20Report%20with%20Cover%20-%20Iowa%20City

A Study of Workforce Characteristics Released October 2010

Iowa City Area Laborshed Analysis

A Project of:

In Partnership with:

For more information regarding the Iowa City Area Laborshed Analysis, contact:

Iowa City Area Development Group

325 East Washington Street, Ste. 101 Iowa City, IA 52240

Phone: 319-354-3939 Fax: 319-338-9958

E-mail: [email protected] E-mail: [email protected]

www.iowacityareadevelopment.com

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Iowa City Laborshed Analysis Iowa Workforce Development, Released October 2010

TABLE OF CONTENTS

Laborshed Analysis 1

Estimating the Total Labor Force Potential 2

Primary Industries of the Laborshed 7

Workforce Statistics 8

Analysis of Those Employed Willing to Change Employment 13

Out-Commuters 21

Estimated Underemployed 22

Willingness of Those Not Currently Employed to Accept Employment 25

Unemployed 26

Homemakers 29

Retired Persons 30

Laborshed Maps

Commuter Concentration by Place of Residence into Iowa City 31

Labor Market Areas in Region: Iowa City Laborshed Area 32

Survey Zones by ZIP Code: Iowa City Laborshed Area 33

Commuter Concentration by Place of Residence into the Amanas 34

Commuter Concentration by Place of Residence into Belle Plaine 35

Commuter Concentration by Place of Residence into Coralville 36

Commuter Concentration by Place of Residence into Hills 37

Commuter Concentration by Place of Residence into Kalona 38

Commuter Concentration by Place of Residence into North Liberty 39

Commuter Concentration by Place of Residence into Oxford 40

Commuter Concentration by Place of Residence into Solon 41

Commuter Concentration by Place of Residence into Swisher 42

Commuter Concentration by Place of Residence into Tiffin 43

Commuter Concentration by Place of Residence into West Branch 44

Commuter Concentration by Place of Residence into West Liberty 45

Exhibits

A. Background Information 49

B. Survey Methodology and Data 50

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C. Current Methods for Estimating Employment & Unemployment 51

D. Occupational Employment Statistics (OES) Category Structure 55

Labor Market Information (Employer-Based) Web Resources 56

References 57

Index of Charts and Tables 58

1


LABORSHED ANALYSIS The purpose of this Laborshed analysis is to measure the availability and characteristics of workers within the region by developing and conducting a telephone survey based on geographic principles. The Laborshed data generated will aid local development officials in their facilitation of industry expansion and recruitment and their service to existing industry in the area. All such entities require detailed data describing the characteristics of the available labor force including current/desired wage rates and benefits, job qualifications and skills, age cohorts, residence/work location, employment requirements/obstacles, and the distances individuals are willing to travel for employment. The first step in determining the potential available labor supply requires an understanding of the Laborshed. Such an understanding will assist local development efforts by delineating the actual geographic boundaries from which communities are able to attract their workers. Determining the area’s Laborshed also builds the foundation for collecting valuable survey data and making estimates concerning the characteristics of the area’s potential labor force. In order to determine the boundaries of the Laborshed area, Iowa Workforce Development (IWD) worked closely with the Iowa City Area Development Group to identify where current employees reside. Employees were then aggregated into ZIP codes and placed into a geographic display for analysis (see Commuter Concentration per ZIP Code map). Applying the mapping function of ArcView Geographic Information System (GIS) software produces the geographic display. This GIS program has been utilized to overlay the ZIP code data set, the county data set and transportation routes. IWD’s database of ZIP code data sets allows for numerous analyses and comparisons of the potential labor force, such as examining the complete demographic data for a ZIP code’s age cohorts (age groupings). Another benefit of applying GIS’s mapping function is the ability to identify visually where the workers are located, concentrations of labor and transportation routes that they use to travel to work. This representation is a valuable tool in understanding the distribution of the labor force within the region. The GIS analysis of the Laborshed area illustrates that segments of the Iowa City Laborshed area are located within a 50-mile radii of the Dubuque (IA), Quad Cities (IA), and Waterloo (IA) Metropolitan Statistical Areas (MSAs), as well as a 30-mile radii of the Burlington (IA), Fort Madison (IA), Grinnell (IA), and Ottumwa (IA) labor market areas (see Labor Market Areas in Region map). These labor centers will have an impact on the size of the area’s labor force and on the attraction of workers from within the Laborshed area. The Laborshed complements existing sources of labor data, such as the U.S. Department of Labor’s Bureau of Labor Statistics (BLS) and the Employment Statistics (ES) and Labor Market Information (LMI) Bureaus of IWD that concentrate on geographic areas based generally on a county or groups of counties. The following sections of this report summarize the results of the Laborshed survey. Due to the magnitude of the survey results, it is not practical to review each set of variables. Instead, IWD has focused on the factors that we have found to be the most valuable to existing and future businesses. However, IWD will certainly conduct additional analyses if the development corporations and/or local businesses desire further review of specific variable(s) or sets of responses.

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ESTIMATING THE TOTAL LABOR FORCE POTENTIAL The fundamental goal of any Laborshed analysis is to estimate the potential availability of workers and determine how well the surrounding geographical areas are able to provide a stable supply of workers to the central Laborshed node (see Table 1). Prior to applying the survey results for the Iowa City Laborshed area, it was necessary to estimate the size of the potential labor force between the ages of 18 and 64 by ZIP code and survey zone. A variety of U.S. Census Bureau, Bureau of Labor Statistics (BLS), Iowa Workforce Development (IWD), and private vendor publications and data sets are used to estimate the size and demographic details of the potential labor force of the Iowa City Laborshed area. A number of adjustments are made to the Iowa City Laborshed area. The first adjustment is to account for differences in the labor participation rates within each of the zones. These adjusted rates are achieved by dividing the labor force cohort between the ages of 18 and 64 by the population cohort between the ages of 18 and 64 (LFC/PC). The labor force cohort includes both employed and non-employed persons that are looking for work. This ratio is similar to the BLS labor force participation rate (LFPR), except that the LFPR includes the total civilian non-institutionalized population age 16 and above. Since most employers are more concerned with the population between the ages of 18 and 64, cohort groups below age 18 and above age 64 are removed. Employment demographic variables such as employment status, age, education level and miles driven to work are taken into consideration when estimating the availability of workers. Of particular interest is the ordinal variable that rates a person’s desire to change employment on a 1-4 scale (1=very likely to change; 4=very unlikely to change). Factors are explored at both the micro (individual) level and at the macro (zip code or Laborshed) level. The estimated total potential labor force is developed using a logistic regression with polytomous response model based on the above covariates drawn from survey data that estimates the theoretical probability of persons accepting or changing employment.

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Table 1 Estimated Total Potential Labor Force

Iowa City Laborshed Area

Total Population 18 to 64

Total Adjusted Labor Force

Total Willing to Change/Accept Employment*

Zone 1IOWA CITY, IA 52240 22,601 22,248 12,553CORALVILLE, IA 52241 11,023 10,851 5,760IOWA CITY, IA 52242 2,477 2,438 1369IOWA CITY, IA 52245 13,573 13,361 7533IOWA CITY, IA 52246 15,039 14,804 8349

Total Zone 1 64,713 63,703 35,564Zone 2AINSWORTH, IA 52201 709 629 304HILLS, IA 52235 10 10 5KALONA, IA 52247 2,975 2,639 1,293LISBON, IA 52253 1,734 1,644 797MARION, IA 52302 17,877 16,946 8,204MOUNT VERNON, IA 52314 3,415 3,237 1,564NORTH LIBERTY, IA 52317 4,430 4,361 2,230OXFORD, IA 52322 1,401 1,379 678RIVERSIDE, IA 52327 1,795 1,592 789SOLON, IA 52333 4,024 3,961 1,991SWISHER, IA 52338 1,804 1,776 870TIFFIN, IA 52340 846 833 424WASHINGTON, IA 52353 4,994 4,430 2,139WELLMAN, IA 52356 1,262 1,119 540WEST BRANCH, IA 52358 2,102 2,091 1,059WILLIAMSBURG, IA 52361 2,200 1,841 885CEDAR RAPIDS, IA 52402 25,617 24,282 11,683CEDAR RAPIDS, IA 52403 14,746 13,978 6,721CEDAR RAPIDS, IA 52404 20,293 19,236 9,267CEDAR RAPIDS, IA 52405 15,468 14,662 7,051COLUMBUS JUNCTION, IA 52738 2,231 1,765 853LONE TREE, IA 52755 1,097 1,080 539MUSCATINE, IA 52761 18,210 15,928 7,733TIPTON, IA 52772 2,866 2,852 1,372WEST LIBERTY, IA 52776 2,522 2,206 1,094WILTON, IA 52778 2,359 2,063 992

Total Zone 2 156,987 146,540 71,077

Weighted Labor Force

Some ZIP codes may not be identified above due to lack of information from the U.S. Census Bureau.

*Total Willing to Change/Accept Employment references those who would be willing to commute into Zone 1 from their home ZIP Code for an employment opportunity

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Table 1 (Cont’d) Estimated Total Potential Labor Force





Zone 3ALBURNETT, IA 52202 626 593 24AMANA, IA 52203 980 820 47ANAMOSA, IA 52205 5,264 4,116 195ATKINS, IA 52206 945 836 42BELLE PLAINE, IA 52208 1,942 1,718 54BROOKLYN, IA 52211 1,487 989 31CENTER POINT, IA 52213 2,360 2,237 85CENTRAL CITY, IA 52214 2,053 1,946 61CLARENCE, IA 52216 785 781 31COGGON, IA 52218 939 890 26CONROY, IA 52220 72 60 3DEEP RIVER, IA 52222 425 283 9ELY, IA 52227 1,129 1,070 69FAIRFAX, IA 52228 944 895 53GARRISON, IA 52229 432 382 10HARPER, IA 52231 248 197 8HIAWATHA, IA 52233 4,119 3,904 222HOMESTEAD, IA 52236 228 191 14KEOTA, IA 52248 1,080 860 36KEYSTONE, IA 52249 500 442 13LADORA, IA 52251 319 267 12LOST NATION, IA 52254 561 487 13LOWDEN, IA 52255 721 717 24MARENGO, IA 52301 2,511 2,102 103MARTELLE, IA 52305 333 260 17MECHANICSVILLE, IA 52306 1,052 1,047 73MIDDLE AMANA, IA 52307 86 72 4MILLERSBURG, IA 52308 46 39 2MONTICELLO, IA 52310 3,509 2,744 98NEWHALL, IA 52315 647 573 24NORTH ENGLISH, IA 52316 916 767 31NORWAY, IA 52318 678 600 32OLIN, IA 52320 753 589 21

Zone 3 Continued




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Zone 3 ContinuedOXFORD JUNCTION, IA 52323 515 403 13PALO, IA 52324 974 923 45PARNELL, IA 52325 454 380 19ROBINS, IA 52328 756 717 38ROWLEY, IA 52329 469 394 11SHELLSBURG, IA 52332 1,256 1,111 42SOUTH AMANA, IA 52334 175 146 11SOUTH ENGLISH, IA 52335 361 287 10SPRINGVILLE, IA 52336 1,447 1,372 52STANWOOD, IA 52337 496 494 26TODDVILLE, IA 52341 636 603 28URBANA, IA 52345 626 554 19VAN HORNE, IA 52346 613 542 19VICTOR, IA 52347 855 716 29VINTON, IA 52349 4,200 3,717 106WALFORD, IA 52351 671 594 38WALKER, IA 52352 1,086 1,029 33WATKINS, IA 52354 214 189 7WEBSTER, IA 52355 193 154 5WEST CHESTER, IA 52359 183 162 9WYOMING, IA 52362 631 493 16CEDAR RAPIDS, IA 52401 1,498 1,420 99CEDAR RAPIDS, IA 52411 3,456 3,276 179BRIGHTON, IA 52540 948 841 28FAIRFIELD, IA 52556 7,736 5,279 131SIGOURNEY, IA 52591 1,629 1,297 36CRAWFORDSVILLE, IA 52621 421 373 20LOCKRIDGE, IA 52635 432 295 8MORNING SUN, IA 52640 870 688 20MOUNT PLEASANT, IA 52641 7,766 5,692 178OLDS, IA 52647 146 107 5SALEM, IA 52649 567 416 11

Zone 3 Continued




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Zone 3 ContinuedWAPELLO, IA 52653 2,205 1,744 54WAYLAND, IA 52654 903 662 23WINFIELD, IA 52659 790 579 22ATALISSA, IA 52720 720 630 57BENNETT, IA 52721 503 500 21BETTENDORF, IA 52722 20,705 17,162 498BLUE GRASS, IA 52726 2,929 2,428 87COLUMBUS CITY, IA 52737 132 104 5CONESVILLE, IA 52739 393 344 26DONAHUE, IA 52746 691 573 17DURANT, IA 52747 1,040 1,035 56ELDRIDGE, IA 52748 4,283 3,550 109FRUITLAND, IA 52749 506 443 15GRANDVIEW, IA 52752 319 252 9LE CLAIRE, IA 52753 2,710 2,246 60LETTS, IA 52754 856 677 24MOSCOW, IA 52760 315 276 21NEW LIBERTY, IA 52765 264 219 8NICHOLS, IA 52766 599 524 50STOCKTON, IA 52769 427 373 18WALCOTT, IA 52773 1,406 1,165 50DAVENPORT, IA 52803 15,298 12,681 388DAVENPORT, IA 52804 16,067 13,318 434DAVENPORT, IA 52806 16,021 13,280 453DAVENPORT, IA 52807 6,954 5,764 180

Total Zone 3 178,006 148,669 5,463Grand Total 399,706 358,912 112,104




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PRIMARY INDUSTRIES OF THE LABORSHED

INDUSTRIES IN THE IOWA CITY LABORSHED AREA - EMPLOYED

In order to provide consistency with other labor market information, the industrial categories identified in this Laborshed analysis will follow a similar format of the Standard Industrial Classification Manual (1987).

Survey respondents from the Iowa City Laborshed area were asked to identify the industry they are currently working. The following information is based on the responses from those Laborshed respondents who are currently employed (Chart 1).

Chart 1 Where the Employed are Working

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WORKFORCE STATISTICS Essentially, when everything else is stripped away, it is the people that are the key to a business’ success (Expansion Management, January 2003) and in nearly all site location studies, labor constitutes one of the most – if not the most – important criterion of the study (AreaDevelopment, April/May 2006). Profiling the characteristics of a community’s Laborshed reveals a very dynamic and diverse collection of skills, abilities, work experience and preferences among residents. It is important to analyze each grouping of respondents to identify and respect their uniqueness and contributions to the Laborshed. The employed individuals who are “very likely” or “somewhat likely” to change jobs within their company, or accept a position with a different employer represent the primary pool of available labor. Many factors must be taken into account when evaluating these workers, such as employment experiences, unused skills, education, wages and benefits desired and the distance individuals are willing to travel to work. Current literature does not suggest standards by which to compare this Laborshed data, however, results from previous Laborshed studies conducted by Iowa Workforce Development (IWD) and the University of Northern Iowa’s Institute for Decision Making (IDM) form a base of comparison for the study. DEMOGRAPHICS OF THE EMPLOYED

The gender breakdown of those respondents, who are employed, is 51.3 percent female and 48.7 percent male. The average age of the employed is 45 years old. A small portion (8.8%) of the employed respondents speaks more than one language in their household. Of those respondents, 53.6 percent speak Spanish. EMPLOYMENT STATUS

The results of this Laborshed survey show that 71.7 percent of all the respondents identified themselves as being employed at the time they were contacted (Chart 2). The majority (75.1%) of the employed are working in positions that are considered full-time (see Chart 3 on the next page).

Chart 2 Employment Status of Survey Respondents

Employed71.7%

Unemployed14.3%

Homemakers7.2%

Retired6.8%

Employed

Unemployed

Homemakers

Retired

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Chart 3 Type of Employment

0%

10%

20%

30%

40%

50%

60%

70%

80%

Full-time Part-time Self -employed Seasonal/Temporary

75.1%

14.7%8.6%

1.4%

Nearly one-tenth (8.6%) of the employed respondents are self-employed. The types of businesses they are operating include construction/handyman (24.3%), personal services (24.3%), child care (18.9%), farming (10.8%), retail (5.4%), artist/writing/music/photography (2.7%), automotive repair/service (2.7%), computer-based business (2.7%), healthcare/social services (2.7%), or professional services (2.7%). The self-employed have been operating their businesses for an average of 15 years, ranging from less than one year to 59 years. EDUCATION & TRAINING

Slightly over three-fourths (75.4%) of the employed residents in the Laborshed area have some level of education/training beyond high school, 4.4 percent are trade certified, 1.4 percent have completed vocational training, 14.4 percent have an associate degree, 23.3 percent have an undergraduate degree, and 17.4 percent have a postgraduate/professional degree. Table 2 provides an overview of the educational fields of study of those who are currently employed in the Laborshed area.

Table 2 Educational Fields of Study

Fields of Study% of

Laborshed

Social Sciences 23.2% Health Care/Medical Studies 15.0% Business, Public Administration, & Marketing 14.2% Business Administrative Support 9.7% Education 9.7% Vocational Trades 8.8% Math & Science 5.3% Engineering & Architecture 4.4% General Studies/Liberal Arts 3.9% Agricultural Studies 3.2% Computer Applications/Programming/Technology 2.6%

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OCCUPATIONS & EXPERIENCES

IWD recodes the respondents’ actual occupations into one of the seven Occupational Employment Statistics (OES) categories. The occupational categories represent a variety of specific occupations held by the respondents (see OES Category Structure - Exhibit D). Classifying the employed by occupational group, Table 3 shows that the largest concentration of the workforce are employed within the professional, paraprofessional, & technical occupational category. The agricultural occupational category represents the smallest sector of workers who are currently employed. The totals are based on the Total Adjusted Labor Force estimates found in Table 1 and the percentage of employed in the Laborshed area.

Table 3

Estimated Workforce by Occupation

Occupational Category% of

Respondents

Potential Total in

LaborshedProfessional, Paraprofessional, & Technical 31.9% 82,091Production, Construction, Operating, Maintenance, & Material Handling

22.8% 58,673

Managerial/Administrative 16.4% 42,204Service 12.0% 30,881Clerical/Administrative Support 11.3% 29,079Sales 5.2% 13,382Agriculture 0.4% 1,029

Total 100% 257,339

Totals may vary due to rounding methods.

Table 4 provides a comparison of the gender distribution within each occupational category.

Table 4 Occupational Categories by Gender

Occupational Category Male Female

Managerial/Administrative 50.6% 49.4%Professional, Paraprofessional, & Technical 37.0% 63.0%Sales 42.9% 57.1%Clerical/Administrative Support 18.5% 81.5%Service 25.9% 74.1%Agriculture 25.0% 75.0%

Production, Construction, Operating, Maintenance, & Material Handling

76.0% 24.0%

Table 5, on the next page, illustrates the percentage of respondents within each occupational category by zone of residence. The table shows that occupational experiences are generally spread across the survey zones. Although Zone 1 is the primary node in the Laborshed area, the table illustrates the impact of the other zones on the extent of available labor. Within most of the occupational categories, the largest percentage of workers may often reside in outlying zones.

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Table 5 Occupational Categories Across the Zones

Occupational CategoryZone 1

% of ZoneZone 2

% of ZoneZone 3

% of Zone

Managerial/Administrative 32.1% 29.6% 38.3%Professional, Paraprofessional, & Technical 42.8% 32.9% 24.3%Sales 42.9% 20.0% 37.1%Clerical/Administrative Support 32.3% 32.3% 35.4%Service 31.8% 38.8% 29.4%Agriculture 25.0% 50.0% 25.0%Production, Construction, Operating, Maintenance, & Material Handling

23.3% 36.3% 40.4%

Equals 100% across the zones

WAGE REQUIREMENTS

Respondents are surveyed on either an hourly or salaried basis; hourly wages are not converted to annual salaries. The Iowa City Laborshed area has a higher concentration of respondents who are currently receiving an hourly wage (56.4%) versus those who are receiving an annual salary (38.0%). The current median wage of those who are employed is $13.50 per hour and the median salary is $52,000 per year. Table 6 provides the current median wages and salaries by industry of the respondents in the Laborshed area. This wage information is an overview of all employed within the Laborshed area without regard to occupational categories or willingness to change employment. If businesses are in need of wage rates within a defined Laborshed area, the survey data can be queried by various attributes to provide additional analysis of the available labor supply. The actual wage levels required by prospective workers will vary between individuals, occupational categories, industries, and economic cycles.

Table 6 Median Wages & Salaries by Industry

No

n

Sal

ary

(per

ho

ur)

Sal

ary

(per

yea

r)

Agriculture * * Construction $ 19.50 * Manufacturing $ 17.00 $ 62,500 Transportation, Communication, & Utilities $ 12.50 $ 53,000 Wholesale & Retail Trade $ 10.88 $ 56,000 Finance, Insurance, & Real Estate * $ 60,000 Professional Services $ 9.75 * Health Care & Social Services $ 13.25 $ 45,000 Entertainment, Recreation, & Personal Services $ 9.76 $ 35,000 Government & Public Administration $ 20.77 $ 80,000 Education $ 12.01 $ 50,000 * Insufficient survey data/refused

Industry

Median Wage and Salary

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Table 7 illustrates current wage rates of those who are currently employed within each defined occupational category.

Table 7

Median Wages & Salaries by Occupational Category

No

n

Sal

ary

(per

ho

ur)

Sal

ary

(per

yea

r)

Managerial/Administrative $ 15.15 $ 53,000 Professional, Paraprofessional, & Technical $ 17.60 $ 59,000 Sales $ 9.51 $ 65,000 Clerical/Administrative Support $ 11.19 $ 35,000 Service $ 11.41 $ 15,000 Agriculture * * Production, Construction, Operating, Maintenance, & Material Handling

$ 15.64 $ 44,000

* Insufficient survey data/refused

Median Wage and Salary

Occupational Category

Wages by gender differ in the Iowa City Laborshed area. The current median hourly wage of employed females in the Laborshed area is $12.00 per hour and the current median hourly wage of employed males is $16.03 per hour. This $4.03 per hour wage difference has females in the Iowa City Laborshed area receiving an hourly wage of 25.1 percent less than males. Females who are receiving an annual salary also are faced with gender wage disparity ($6,500 per year). Currently females are making a median annual salary of $50,000 per year while males are making a median salary of $56,500 a year. This results in an 11.5 percent difference in annual salaries. EMPLOYMENT BENEFITS

There are a variety of benefit packages being offered to employees within the Iowa City Laborshed area in addition to wages. Current benefits include health/medical insurance (93.2%), pension/retirement options (70.0%), dental coverage (58.8%), paid vacation (54.0%), vision coverage (40.7%), paid holidays (35.6%), life insurance (30.3%), paid sick leave (25.5%), disability insurance (21.7%), prescription drug coverage (17.8%), paid time off (13.1%), flextime (3.6%), shift differential pay (2.1%), incentive reward programs (1.8%), health club/fitness membership (1.2%), stock options (1.2%), tuition assistance/reimbursement (1.2%), child care (0.6%), and hiring bonuses (0.3%). Nearly four-fifths (77.8%) of the respondents in the Laborshed area state they are currently sharing the premium costs of health/medical insurance with their employer, 13.8 percent indicate their employer covers the entire cost of insurance premiums while 7.7 percent indicate they have made other arrangements. COMMUTING

Commuting data collected by the Laborshed survey assists developers and employers in understanding how employed residents can/could commute within/out of the area. Overall, individuals are commuting an average of 9 miles one way for employment opportunities. Those who live in Zone 1 are commuting an average of 6 miles one way, while residents in Zone 2 are commuting an average of 9 miles one way, and Zone 3 residents are commuting an average of 12 miles one way for employment. Keep in mind that for those residing in Zones 2 and 3 commuting distances of less than 20 miles one way may or may not get them into the nodal community (Iowa City).

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ANALYSIS OF THOSE EMPLOYED WILLING TO CHANGE EMPLOYMENT

Analyzing the employed based on their willingness to change employment creates a profile of individuals interested in changing from their current position. The data shows that 25.1 percent of those who are currently employed within the Laborshed area indicated they are either “very likely” or “somewhat likely” to change employers or employment if presented with the right job opportunity. Job satisfaction is the primary reason that those who are currently employed are not willing to consider changing employment. A good working relationship with current employer, benefits, age near retirement, wages, job security, seniority, employment location close to home, flexibility of work hours, a good working relationship with current coworkers, lack of job opportunities, family reasons, and self-employed are other reasons mentioned but not as frequently. Table 8 shows the employed willing to change employment residing throughout the survey zones. Respondents willing to change employment by zone are calculated using a logistic regression model weighted by multiple variables such as education level, gender, age, miles willing to travel, and wages. This model provides an estimate for the total number of individuals “willing to change” by zone. The totals are based on the Total Adjusted Labor Force estimates found in Table 1.

Table 8 Totals by Zone

Total Adjusted Laborforce by

Zone

Estimated Total Willing to Change/Accept by

Zone*

Estimated Number of Employed Willing to

Change by Zone*

Zone 1 63,703 35,564 30,165Zone 2 146,540 71,077 60,882Zone 3 148,669 5,463 4,455

Total 358,912 112,104 95,502*Total Willing to Change/Accept Employment references those who would be willing to commute into Zone 1 from their home ZIP code for an employment opportunity.

Slightly over one-tenth (10.2%) of those who are employed, willing to change employment, are working two or more jobs. This group would prefer to work full-time hours for one employer versus working for multiple employers to accomplish full-time employment. Those who are employed willing to change are currently working an average of 41 hours per week. One-fourth (25.0%) would consider employment offers that require them to work more hours. Further analysis finds that 85.5 percent would prefer to work full-time positions (35+ hrs./week), while 14.5 percent prefer positions with less than full-time hours. Temporary and seasonal employment opportunities do not appeal to the majority of those who are currently employed and willing to change employment. Seasonal employment would interest 36.1 percent, while 27.8 percent would consider a temporary employment offer. When asked about their interest in entrepreneurship opportunities, 37.0 percent of the employed, that are willing to change employment, expressed an interest in starting a business. The types of businesses they are primarily interested in starting include construction/handyman (15.8%), retail (15.8%), personal services (13.2%), restaurant (13.2%), child care (10.5%), automotive repair service (7.9%), and computer-based business (5.3%). However, the majority find access to capital/start-up funds is the primary impediment of operating their own business

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venture followed by time requirements, development of a business plan, concern about the economy, finding a prime business location, marketing expertise, insurance issues, and risk involved. AGE AND GENDER OF THE EMPLOYED

The gender breakdown of those willing to change employment is distributed 50.9 percent male and 49.1 percent female. Table 9 compares the gender distribution among the employed respondents willing to change employment in each zone. These calculations are based on the Estimated Number of Employed Willing to Change of 95,502 projections found in Table 8.

Table 9 Estimated Totals by Zone & Gender

Female Male Female Male Female Male % of Zone 43.9% 56.1% 54.3% 45.7% 50.0% 50.0% Estimated Total by Zone 13,242 16,923 33,059 27,823 2,228 2,228Totals may vary due to rounding methods.

Zone 1 Zone 2 Zone 3

The average age of those willing to change employment is 42 years of age. Table 10 provides a breakdown by age category of the employed respondents who are willing to change employment. These calculations are based on the Estimated Number of Employed Willing to Change of 95,502 projections found in Table 8.

Table 10

Age Range Distribution

Age Range% of

Respondents

Potential Total in

Laborshed18 to 24 2.9% 2,77025 to 34 18.5% 17,66835 to 44 37.0% 35,33645 to 54 25.9% 24,73555 to 64 15.7% 14,994

Total 100% 95,503Totals may vary due to rounding methods.

EDUCATION & TRAINING

The survey results show that 73.1 percent of the respondents willing to change employment have some level of education/training beyond high school, 1.9 percent are trade certified, 0.9 percent have completed vocational training, 14.8 percent have an associate degree, 24.1 percent have an undergraduate degree, and 14.8 percent have a postgraduate/ professional degree. As with other segments of the Laborshed study, education levels vary by industrial and occupational categories, gender and age groups. Additional data can be provided for specific inquiries regarding education and training by contacting the Iowa City Area Development Group.

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Table 11 provides an overview of the educational fields of study for those who are employed and willing to change employment.

Table 11 Educational Fields of Study

Fields of Study% of

Laborshed

Social Sciences 29.2% Business, Public Administration, & Marketing 17.7% Health Care/Medical Studies 11.4% Vocational Trades 10.1% Education 10.1% Business Administrative Support 8.9% Engineering & Architecture 3.8% General Studies/Liberal Arts 2.5% Computer Applications/Programming/Technology 2.5% Math & Science 2.5% Agricultural Studies 1.3%

Education and training are the keys to successful careers and employment opportunities. Half (50.0%) of the employed, willing to change employment, realize to make a successful transition to new employment or be promoted within their current organization, they will need additional education/training. Those respondents desire to start/finish college degree (38.2%), attend computer courses (25.5%), obtain continuing education units “CEU’s” (9.1%), participate in on-the-job training (3.6%), and complete vocational training (1.8%). The primary areas of computer training which they want to take are software classes (Office, Word, etc.) (40.0%), general computer operations (keyboarding, etc.) (33.3%), and programming (COBOL, JAVA, network administration, etc.) (26.7%). Over one-fourth (27.3%) are likely to seek additional training/education in their specified areas of study within the next year. Community and economic developers, college/university professionals, and human resource professionals may use this information as a guide for determining and enhancing their workforce education and training programs. Additional issues influencing education/training programs may include class time, cost, and location. OCCUPATIONS & EXPERIENCES

IWD recodes the respondents’ actual occupations into one of the seven Occupational Employment Statistics (OES) categories. The occupational categories represent a variety of specific occupations held by the respondents (see OES Category Structure - Exhibit D). Classifying the employed by current occupations and likeliness to change, Table 12 (on next page) shows that the largest concentration of potential available labor is employed within the production, construction, & material handling occupational category. The sales occupational category represents the smallest sector of workers willing to change employment. The calculations for potential available labor are based on the Estimated Number of Employed Willing to Change of 95,502 projections found in Table 8.

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Table 12 Estimated Workforce by Occupation

Occupational Category% of

Respondents

Potential Total in

LaborshedProduction, Construction, Operating, Maintenance, & Material Handling

25.2% 24,067

Professional, Paraprofessional, & Technical 23.4% 22,347Clerical/Administrative Support 16.8% 16,044Service 13.1% 12,511Managerial/Administrative 12.1% 11,556Sales 9.4% 8,977Agriculture * *

Total 100% 95,502* Insufficient survey data

Table 13 provides a comparison of those willing to change employment by gender. The Iowa City Laborshed area has a higher percentage of males who are employed willing to change than females (50.9% and 49.1% respectively). Employers within the Laborshed area looking to fill positions can utilize this information to more efficiently focus their recruitment efforts in the occupational categories from which they plan to hire.

Table 13 Occupational Categories by Gender

Occupational Category Male Female

Managerial/Administrative 46.2% 53.8%Professional, Paraprofessional, & Technical 44.0% 56.0%Sales 40.0% 60.0%Clerical/Administrative Support 38.9% 61.1%Service 21.4% 78.6%Agriculture * *Production, Construction, Operating, Maintenance, & Material Handling

85.2% 14.8%

* Insufficient survey data

The occupational categories encompass a wide variety of individual occupations in which workers in the Laborshed area are employed. In some cases, workers willing to change positions may be employed in jobs that do not maximize all of their available skills and work experiences. Employees may possess talents that go unutilized or unrecognized by their current employer. Employers tapping into this resource may be effective in attracting employees to different positions or increasing their value to the company. For a list of current or previous occupational titles and experiences in the Iowa City Laborshed area, contact the Iowa City Area Development Group. Employers may be aided in their recruiting efforts by being able to identify the respondents by their occupation and area of residence. Table 14, on the next page, illustrates the percentage of respondents in each occupational category within each Laborshed zone. The table shows that the occupational experiences are generally spread across the survey zones, but the outlying zones have a substantial effect on a community’s in-commute, thus affecting many

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economic factors. For the most part, employers looking to fill positions within these occupational categories may want to expand their recruitment efforts to include communities surrounding Iowa City.

Table 14 Occupational Categories Across the Zones

Occupational CategoryZone 1

% of ZoneZone 2

% of ZoneZone 3

% of Zone

Managerial/Administrative 30.8% 46.2% 23.0%Professional, Paraprofessional, & Technical 52.0% 20.0% 28.0%Sales 50.0% 30.0% 20.0%Clerical/Administrative Support 27.8% 27.8% 44.4%Service 57.1% 28.6% 14.3%Agriculture * * *Production, Construction, Operating, Maintenance, & Material Handling

22.2% 40.7% 37.1%

Equals 100% across the zones

* Insufficient survey data Table 15 details the occupational categories the residents would consider seeking employment by survey zone of residence. This information can provide businesses, community developers, and leaders a “snapshot” for future community growth.

Table 15

Desired Occupational Categories Within the Zones

Desired Occupational CategoryZone 1

% of ZoneZone 2

% of ZoneZone 3

% of Zone

Managerial/Administrative 14.3% 12.5% 14.3%Professional, Paraprofessional, & Technical 60.7% 29.2% 25.0%Sales 3.6% 12.5% 3.6%Clerical/Administrative Support 14.3% 12.5% 21.4%Service 7.1% 12.5% 14.3%Agriculture * * *Production, Construction, Operating, Maintenance, & Material Handling

0.0% 20.8% 21.4%

Equals 100% within the zone

* Insufficient survey data As Table 15 notes, those who are employed within the Iowa City Laborshed area who are willing to change employment are looking for a wide variety of employment opportunities. However, the majority of those who reside in Zone 1 (Iowa City) are looking for positions within the professional, paraprofessional, & technical occupational category (approximately 18,310 people). Those who reside in Zones 2 and 3 are also primarily looking for positions within the professional, paraprofessional, & techincal occupational category (approximately 17,778 people in Zone 2 and 1,114 people in Zone 3). Projections are based on zone totals obtained from Table 8.

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WAGE REQUIREMENTS

Table 16 provides data concerning the employed respondents’ current median wages and salaries, by their likeliness to change employment. Additional data from the survey can be analyzed to provide businesses a benchmark for determining wage rates in the Laborshed area. The actual wage levels required by prospective workers will vary between individuals, occupational categories, industries, and economic cycles. Nearly three-fifths (57.4%) are hourly wage earners.

Table 16

Comparison of Current Wage Data All

EmployedThose Likely

to ChangeThose Unlikely

to Change Current Wage:

Median (hourly) $13.50 $12.00 $15.00

Current Salary:

Median (yearly) $52,000 $45,000 $52,000 As Table 16 shows there is a disparity between the median hourly wages and median annual salaries of respondents likely to change employment and those content with their current position ($3.00/hr or $7,000/yr). Those who changed jobs in the past year cited employer layoff/relocation (25.0%), better wages (22.2%), respondent moved (16.7%), better benefits (8.3%), respondent was fired from previous employment (8.3%), personality conflicts with former employer/coworkers (8.3%), and employment was temporary/seasonal (8.3%) as the primary reasons for change. The wage threshold of employed residents who are “very likely” or “somewhat likely” to change employment is estimated to be $15.00 to $15.50 per hour regardless of industry. Salaried employees willing to change employment have a threshold of $60,000 to $70,000 per year. Table 17 reflects those who are currently employed willing to change and the estimated wage range required to attract 66 percent to 75 percent of the most qualified hourly wage applicants by industry.

Table 17 Wage Threshold by Industry

Agriculture *Construction *Manufacturing $16.46 - $18.25Transportation, Communication, & Utilities $12.15 - $12.38Wholesale & Retail Trade $14.04 - $15.50Finance, Insurance, Real Estate, & Professional Services $10.00 - $10.50Health Care & Social Services $13.84 - $20.00Entertainment, Recreation, & Personal Services $13.80 - $16.50Government & Public Administration *Education $17.40 - $18.00

Industry

Wage Threshold

No

n

Sal

ary

(per

ho

ur)

*Insufficient data collected to provide thresholds due to the limited number of hourly wage earners likely to change employment in those industries.

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Another comparison to consider is the employed respondents’ lowest wages considered based on gender. Table 18 provides the lowest wages considered between the genders.

Table 18 Comparison of Lowest Wages Considered by Gender

Male Female

Lowest Wage Considered: Median (hourly) $15.00 $11.00

Lowest Salary Considered: Median (yearly) $50,000 $41,000

In many Laborshed areas, there is a discrepancy between the lowest wages considered of males and females. This falls true in the Iowa City Laborshed area when looking at hourly wage rates of those who are willing to change employment without regard to specific industry. The lowest median hourly wage that females would consider is 26.7 percent less than that of males. Likewise, the median salary females would consider is 18.0 percent less than that of males. Some of the disparity may be explained by the differences in the occupational and industrial categories of the respondents, nevertheless discrepancies still exist. EMPLOYMENT BENEFITS

The survey provides the respondents an opportunity to identify employment benefits that would influence their decision to change employment. Desired benefits include health/medical insurance (94.5%), pension/retirement options (56.0%), paid vacation (51.6%), dental coverage (45.1%), vision coverage (28.6%), paid holidays (25.3%), paid sick leave (24.2%), life insurance (17.6%), disability insurance (9.9%), prescription drug coverage (9.9%), paid time off (7.7%), flextime (5.5%), incentive rewards programs (4.4%), health club/fitness memberships (2.2%), hiring bonuses (2.2%), shift differential pay (2.2%), tuition assistance/reimbursement (2.2%), and stock options (1.1%). For some respondents, benefits offered in lieu of higher wages can be the driving force to change employment. Some respondents assume that particular benefits, such as health/medical insurance, would be incorporated into most standard employment packages; therefore, they did not select health/medical as an influential benefit option. When contemplating a change in employment, one-third (33.3%) of those surveyed would prefer to look for offers where the employer covers all the premium costs of health/medical insurance while the majority (61.9%) would be willing to cost share the premium for health/medical insurance with their employer. Over three-fourths (77.5%) of those who are employed willing to change state they are currently sharing the premium costs of health/medical insurance with their employer and 7.0 percent indicate their employer is covering the entire cost of health/medical insurance. When it comes to considering influential benefit options to employment offers, there is a difference between those who currently share in the costs of medical insurance premiums to that of those who desire cost sharing of medical insurance premiums. This leads to the belief that cost sharing versus employer paid would influence the employed to change positions or companies. FLEXIBILITY & ADAPTABILITY IN THE WORKPLACE

The Laborshed area residents are very receptive to various work environments. Most respondents (87.0%) are willing to work in an environment that offers team environments, groups of individuals coming together to accomplish a common goal; 74.1 percent would prefer to work in cross-training opportunities, training to do more than one job; and over one-fourth (25.9%) would consider job sharing work arrangements, involving two or more individuals

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splitting one full-time job. As such arrangements become more common in the workplace; more and more employees are expressing greater interest. Employment opportunities that require a variety of work schedules (combinations of 2nd, 3rd or split shifts) would pique the interest of 28.7 percent of the employed that are willing to change employment. JOB SEARCH TECHNIQUES

Employers who have a clear understanding of the job search resources used by workers will improve their ability to maximize their effectiveness and efficiency in attracting qualified applicants. Residents living in the Iowa City Laborshed area are undoubtedly exposed to numerous sources by which employers communicate job openings and new hiring. Therefore, it is important to understand what sources potential workers rely on when looking for jobs. The most frequently identified job search resources are the internet (75.0%), local newspapers (47.1%), networking (31.7%), local Iowa Workforce Development Centers (25.0%), and regional newspapers (11.5%). College/university career centers, private employment services, television, walk-in (door-to-door) solicitation, job/career fairs, trade publications, and radio were also mentioned but less frequently as utilized sources for employment opportunities. Those utilizing the local newspaper tend to seek employment opportunities by searching in their hometown news publication. The most popular local/regional newspaper sources include The Gazette – Cedar Rapids, Quad City Times, and Iowa City Press Citizen. The internet is host to many sources for employment opportunities, the most commonly used sites to look for employment opportunities in the Iowa City Laborshed are www.monster.com, www.careerbuilder.com, and www.iowaworkforce.org. The type of industry the individual is seeking to be employed may determine the sources used. Businesses wanting more detailed advertising sources may contact the Iowa City Area Development Group. Understanding and utilizing traditional and non-traditional advertising media will provide employers a more focused and effective recruitment tool. COMMUTING

Commuting data collected by the Laborshed survey assists developers and employers in understanding how employed residents that are willing to change employment can/could commute within/out of the area. Overall, the employed willing to change would commute an average of 22 miles one way for employment opportunities. Those who live in Zone 1 are willing to commute an average of 21 miles one way, while residents in Zone 2 are willing to commute an average of 22 miles one way and Zone 3 residents are willing to commute an average of 25 miles one way for the right employment opportunity. To provide a comparison, those employed willing to change as well as those employed but not willing to change, are currently commuting an average of 9 miles one way to work. Where individuals live within the Laborshed will influence their desire to commute to the node community. The node community may be the largest economic center for many of the smaller communities in the area. Individuals from the surrounding communities seeking job opportunities and competitive wages/benefits may be resigned to the fact that they will have to commute some distance to a new employer. In these cases, the willingness of the Zone 2 and 3 respondents to commute a substantial distance increases the likelihood that they may be interested in commuting (or interested in continuing to commute) to the node community. However, the willingness of Zone 1 residents to commute represents a potential out commute from the node community. This point illustrates the influence of surrounding labor on the individual Laborsheds - potentially drawing workers out of the node (see Labor Market Areas in Region map).

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OUT COMMUTERS The out commute of a community represents the percentage of residents living in the node community (Iowa City/Coralville), but working for employers located in other communities. The out commute for Iowa City/Coralville is estimated at 20.1 percent – approximately 9,219 people living in Iowa City or Coralville who work in other communities. Most of those who are out commuting are working in Cedar Rapids or North Liberty. Of those who are commuting to other communities for employment opportunities, 31.0 percent are willing to change employment (approximately 2,858 people) if presented with the right employment offer. The calculations for potential available labor are based on adjusted labor force zone totals obtained from Table 8. As a group, they are primarily employed within the professional, paraprofessional, & technical; managerial; clerical; or production, construction, & material handling occupational categories. They are primarily working within the education; manufacturing; and construction industries. For those who out commute, 93.1 percent have education/technical training beyond high school, 6.9 percent are trade certified, 13.8 percent have an associate degree, 27.5 percent have an undergraduate degree, and 34.5 percent have a postgraduate/professional degree. Areas of emphasis include business/public administration, marketing, general/liberal arts, social sciences, and education. Over three-fourths (75.9%) of those who are commuting out of Iowa City/Coralville for employment are salaried employees whose current median income is $61,500 per year Hourly wage employees (24.1%) have a median wage of $12.13 per hour. Out commuters are currently commuting an average of 15 miles one way to work, and are willing to commute an average of 17 miles for a “new opportunity”. Nearly three-fourths (72.4%) of out commuters are male. The average age of out commuters is 47; however, over one-third (34.5%) are between the ages of 55 and 64.

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ESTIMATED UNDEREMPLOYED Underemployment is a recent point of interest in popular literature, but has actually been an issue studied and addressed by economists for nearly 20 years. While there is no one widely accepted definition of underemployment for the purpose of this Laborshed study, underemployment is defined in the following three ways: 1. Inadequate hours worked -- individuals working less than 35 hours per week and desiring

more hours. 2. Mismatch of skills -- workers are denoted as “mismatched” if their completed years of

education are above the number needed for their current occupational group, they have significant technical skills beyond those currently being utilized, or if they have held previous jobs with a higher wage or salary.

3. Low income -- individuals working full-time but at wages insufficient enough to keep them

above the poverty level. Each of these categories of underemployment can be very difficult to estimate; however, it appears as though elements of each of these categories exist in this Laborshed area. UNDEREMPLOYED DUE TO INADEQUATE HOURS WORKED

In order to assess the impact of underemployment by inadequate hours worked in the Laborshed area, we refer to tabulations of the employed willing to change employment working 34 hours or less from the survey responses. The survey data shows that underemployment due to inadequate hours is estimated to be 2.0 percent within the Laborshed area (Table 19).

Table 19 Underemployed Due to Inadequate Hours Worked

Percent Underemployed Low Hours

Estimated Underemployed Desiring More Hours

2.0% 1,910

The calculation for estimated underemployed desiring more hours is based on the Estimated Number of Employed Willing to Change 95,502 projections found in Table 8. Two-thirds (66.7%) of those who are considered to be underemployed due to low hours in the Iowa City Laborshed are female. Those who are underemployed due to inadequate hours have an average age of 41 years old. Additionally, those who are underemployed due to inadequate hours are currently employed within the service; production, construction, & material handling; managerial; clerical; professional, paraprofessional & technical; or sales occupational categories and are currently seeking employment opportunities within the professional, paraprofessional & technical; production, construction, & material handling; clerical; or managerial occupational categories. This group is willing to commute an average of 20 miles one way for the right employment opportunity. Two-thirds (66.7%) of the respondents who are underemployed due to inadequate hours have an education beyond high school. Businesses may want to look inside their own organizations for potential candidates when looking to fill openings requiring full-time employment status.

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UNDEREMPLOYED DUE TO MISMATCH OF SKILLS

Underemployment may also be calculated by examining individuals that are employed in positions that do not maximize their previous experience, skills and education, or that do not adequately compensate them based on their qualifications. IWD’s Laborshed survey of the region attempts to provide the best estimate of this “mismatch” of skills by asking respondents if they believe that they are underemployed and if so, why. Respondents first answered the question, “Are you qualified for a better job?” Individuals answering “yes” are then asked to classify why they are qualified based on categories relating to previously held jobs that required more skill and education, acquiring additional job training and education at their current job, current job does not require their level of training or education and greater pay at a previous job. Respondents selected all descriptors that applied to their situation. The choices provided on the survey are not an exhaustive list of explanations of why the respondent is overqualified, but a collection of the most likely responses based on prior surveys and research. The respondents’ results are then applied to the entire Laborshed area to analyze why underemployment by mismatch of skills exists. IWD then conducts a second method of validating whether or not underemployment by mismatch of skills actually exists. Each time a respondent lists a reason for why he or she is qualified for a better job, other survey questions are analyzed to estimate whether the person is truly underemployed, or simply overstating their skills and education or underestimating the requirements of the labor market. For example, if a respondent states that they are underemployed because they previously held a job that required more skill and education, IWD evaluates the person’s current employer type, occupation type, skills unused at their current position, age, employment status, education, years in current position, and the type of job they would consider to see if they are consistent with the person’s underemployment. Table 20 shows that 3.2 percent are underemployed due to mismatch of skills. If a respondent is determined to be underemployed due to mismatch of skills for more than one of the four reasons, that individual is only counted once for the Estimated Underemployed and for the Potential Total figures. The calculation for Potential Total in Laborshed figure is based on the Estimated Number of Employed Willing to Change of 95,502 projections found in Table 8. Additionally, all employed respondents are filtered to include only those that identified that they are “very or somewhat likely” to accept employment when calculating underemployment. This filtering reflects the belief that a respondent is not accurately representing himself or herself as underemployed when they are unwilling to accept new employment opportunities that could improve their status.

Table 20 Underemployed Due to Mismatch of Skills Estimated Underemployed due to Mismatch of Skills

Potential Total in Laborshed

3.2% 3,056

Zone 1 contains 42.1 percent of those who are underemployed due to mismatch of skills, Zone 2 also contains 42.1 percent, and Zone 3 contains 15.8 percent in the Iowa City Laborshed area. In many rural areas, mismatch of skills tends to be higher because of the desire to maintain a certain level of quality of life issues. Over half (52.6%) of those who are considered to be underemployed due to mismatch of skills in the Iowa City Laborshed are male. The education level obtained compared to occupation previously held provides the greatest discrepancy when looking at mismatch of skills. The majority (94.7%) have some education

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beyond high school, 26.3 percent have an associate degree, 47.3 percent have an undergraduate degree, and 10.5 percent have a postgraduate/professional degree. They are willing to commute an average of 21 miles one way for employment opportunities within the professional, paraprofessional, & technical; production, construction, & material handling; clerical; sales; service; and managerial occupational categories. UNDEREMPLOYED DUE TO LOW INCOME

Measuring underemployment by low income is accomplished by determining how many households in the Laborshed area fall below the poverty level. A total of 1.5 percent of the respondents answering the household income question fall below the 2009 federal poverty thresholds based on their household income and number of members living in the household (i.e., based on a family of four, the annual household income guideline is $22,050). Table 21 provides an overview of the survey respondents who fall below the 2009 federal poverty level and the potential number affected in the Laborshed area that are underemployed due to low income.

Table 21 Underemployed Due to Low Income

Percent Underemployed Due to Low Income

Potential Underemployed Due to Low Income

1.5% 1,433

The calculation for potential underemployment due to low income is based on the Estimated Number of Employed Willing to Change of 95,502 employment projections found in Table 8. TOTAL ESTIMATED UNDEREMPLOYED

All three measures of underemployment result in an estimated total underemployment rate of 5.0 percent in the Laborshed area (Table 22). It is important to emphasize that these underemployment percentages are only estimates; however, IWD has filtered the data to eliminate double counting of respondents within and between the three categories. A person underemployed due to inadequate hours and mismatch of skills is only counted once.

Table 22 Total Estimated Underemployed

Percent Underemployed by Inadequate Hours

Percent Underemployed by Mismatched Skills

Percent Underemployed by Low Income

Percent Total Estimated

Underemployment

2.0% 3.2% 1.5% 5.0%

The wage threshold for the underemployed is $12.18 to $15.00 per hour with a lowest median considered wage of $11.00 per hour. When looking for employment opportunities the underemployed use the internet (73.3%); local newspapers (46.7%); networking through friends, family, and/or acquaintances (33.3%); local Iowa Workforce Development Centers (16.7%); regional newspapers (6.7%); college/university career centers (6.7%); job/career fairs (3.3%); television (3.3%); and walk-in (door-to-door) solicitation (3.3%) as the preferred job search media.

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WILLINGNESS OF THOSE NOT CURRENTLY EMPLOYED TO ACCEPT EMPLOYMENT

The BLS defines unemployed persons as individuals who are currently not employed but that are actively seeking employment. Using only this definition overlooks sources of potential labor, specifically homemakers who are not employed and retirees who, though currently not employed, would consider entering or re-entering the workforce if the right opportunity arose. IWD uses an alternative definition “not employed” for its Laborshed studies which includes the unemployed, homemakers/not employed, and retirees as subsets of the category. The survey asks the respondents to identify whether they are unemployed, a homemaker/not employed or retired. It is useful to look at the specific characteristics of each of these subsets of “not employed” persons. The inclusion of these subset groups into the analysis provides a more accurate assessment of the potential labor force in the Laborshed area. Of the respondents surveyed, 28.3 percent reported that they are “not employed”. By questioning these respondents about their willingness to re-enter or accept a job offer, the survey identified 44.7 percent who stated they are “very likely” or “somewhat likely” to accept employment. Aggregated totals for the “not employed” may be achieved by combining the data from any or all of Tables 23, 24, and 25. Each of the “not employed” subsets has their own unique characteristics that define their contribution to the Laborshed area. Recognizing and understanding these factors will aid in efforts to target and tap into this often unrecognized and underutilized labor resource. The following sections provide a profile of the unemployed, not employed homemakers, and retired respondents.

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UNEMPLOYED Of those who responded to being unemployed, 58.1 percent are “very likely” or “somewhat likely” to accept employment if the right opportunity arose. Table 23 shows that the unemployed reside across all three zones of the Laborshed area. Respondents willing to accept employment by zone are calculated using a logistic regression model weighted by multiple variables such as education level, gender, age, miles willing to travel, and wages. This model provides an estimate for the total number of individuals “willing to change” by zone. The totals are based on the Total Adjusted Labor Force estimates found in Table 1 (approximately 4,391 unemployed persons).

Table 23 Unemployed - Willing to Accept Employment


Zone


Zone*

Estimated Number of Unemployed Willing to Accept by Zone*

Zone 1 63,703 35,564 1,802Zone 2 146,540 71,077 2,319Zone 3 148,669 5,463 270


The current methods to determine the unemployment rate exclude those who have been unemployed longer than six months, those who did not register with the unemployment office and students who are seeking employment. The Laborshed unemployed percent includes anyone who stated they were unemployed then incorporates all counties within the Laborshed area, where as the unemployment rate only takes into consideration individual counties. DEMOGRAPHICS OF THE UNEMPLOYED

The average age of this group is 41 years old. The unemployed respondents are distributed amongst all of the age range groups, 18 to 24 (10.0%), 25 to 34 (30.0%), 35 to 44 (14.0%), 45 to 54 (26.0%), and 55 to 64 (20.0%). The gender breakdown of those unemployed is 56.0 percent female and 44.0 percent male. EDUCATION & TRAINING

Three-fifths (60.0%) of the unemployed respondents in the Iowa City Laborshed area have some post high school education, 6.0 percent are trade certified, 2.0 percent have completed vocational training, 10.0 percent have an associate degree, 16.0 percent have an undergraduate degree and 10.0 percent have a postgraduate/professional degree. Over one-fourth (28.0%) of those who are unemployed and willing to re-enter the workforce feel they need additional training/education in order to make a successful transition back into the workforce. They would like to attend computer training (35.3%), start/finish college degree (17.6%), obtain continuing education units “CEU’s” (11.8%), attend vocational training (11.8%), and participate in job preparedness classes (11.8%). Financing is the main obstacle preventing them from pursuing additional education/training.

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WORK EXPERIENCE & ENVIRONMENT

Over half (54.0%) of the respondents became unemployed within the last year with the majority (75.5%) of those having held full-time positions, while 14.3 percent held part-time positions, and 10.2 percent held temporary positions in their previous employment. These individuals have diverse work experiences; the majority held positions within the production, construction, & material handling; service; sales; managerial; professional, paraprofessional, & technical; or clerical occupational categories. A variety of explanations were given as to why the respondents are unemployed at this time. The most frequently mentioned responses include employer layoff/relocation (36.0%), disability issues (10.0%), lack of employment opportunities (10.0%), temporary/summer employment (10.0%), family reasons (8.0%), or respondent was fired from previous employment (6.0%). Nearly three-fifths (58.0%) of the respondents who are unemployed are seeking/have sought services to gain employment. Of those, over four-fifths (82.1%) are utilizing the local Iowa Workforce Development Centers to assist in seeking qualified offers and plan to seek jobs within the production, construction, & material handling; professional, paraprofessional, technical; service; managerial; and clerical occupational categories. The unemployed respondents can accommodate a variety of work environments. The majority (90.0%) of the respondents expressed an interest in job team work environments, 88.0 percent of the respondents would prefer employment opportunities that provide cross-training, and 64.0 percent would be interested in job sharing positions - two people sharing one full-time position. Over three-fifths (62.0%) of the unemployed expressed an interest in working a variety of work schedules (combinations of 2nd, 3rd or split shifts). Seasonal employment opportunities would interest 78.0 percent of those who are unemployed, while temporary employment would be a consideration for 76.0 percent of the unemployed looking to re-enter the workforce. Nearly one-fourth (24.4%) of those who are unemployed, willing to re-enter, would consider starting their own business. The businesses they are primarily interested in starting include restaurant (30.0%), construction/handyman (10.0%), and personal services (10.0%). Access to start-up funds is the primary obstacle preventing them from pursuing their entrepreneurial venture. Keep in mind that not all of those who stated they had an interest will actually pursue an entrepreneurial venture. What this does show is that a certain level of entrepreneurial ambition is present in the area that can be captured in the workplace environment. WAGES & BENEFITS

Wage levels, hours available, and employee benefits are important factors for unemployed individuals. The estimated wage threshold for the unemployed willing to re-enter employment is $10.00 to $11.00 per hour. This threshold should serve as a base recommendation for obtaining the most qualified applicants for hiring. The median of the lowest hourly wage that unemployed respondents are willing to accept is $9.00 per hour. At their prior employment, the unemployed received a median hourly wage of $10.25 per hour. In addition to salary/wages and hours, some of the unemployed would be influenced by the following benefits when considering an employment offer: health/medical insurance (87.8%), dental coverage (43.9%), paid vacations (39.0%), pension/retirement options (31.7%), paid holidays (24.4%), vision coverage (19.5%), paid sick leave (12.2%), disability insurance (7.3%), life insurance (7.3%), prescription drug coverage (7.3%), paid time off (2.4%), and tuition assistance/reimbursement programs (2.4%). In some situations, benefits offered will play a deciding factor in whether the unemployed accept a position. One such example would be companies that offer cost sharing of medical insurance benefits. Two-thirds (66.7%) of those

28


seeking to return to the workforce would prefer employment offers that include medical insurance where the employer and employee share the cost of the premiums. JOB SEARCH TECHNIQUES

When looking for employment opportunities, unemployed persons generally rely on common and easily accessible sources of information; however, non-traditional methods are also being utilized in order to locate the “right opportunity”. The most frequently identified job search media are the internet (73.5%); local newspapers (51.0%); local Iowa Workforce Development Centers (36.7%); networking through family, friends, and acquaintances (24.5%); walk-in (door-to-door) solicitation (20.4%); regional newspapers (10.2%); bulletin boards (4.1%); private employment services (4.1%); college/university career centers (2.0%); radio (2.0%); and vocational rehabilitation services (2.0%). To provide businesses and community leaders with a more in-depth focus on advertising sources currently being used by the unemployed willing to re-enter the workforce, the Iowa City Press Citizen, Quad City Times, and The Gazette – Cedar Rapids are the primary print sources, while www.iowaworkforce.org, www.craigslist.org, and www.careerbuilder.com are the primary internet sources viewed by those seeking employment in the Iowa City Laborshed area. COMMUTING

The average number of miles that unemployed respondents are willing to travel one way to work is 21 miles. Zone 1 respondents are willing to commute an average of 19 miles one way to work, Zone 2 respondents are also willing to commute an average of 19 miles one way to work, and Zone 3 respondents are willing to commute an average of 25 miles one way to work. Since some Zone 1 unemployed residents are willing to commute great distances, once employed, they could become part of the out commuting of the nodal community. The unemployed in the Laborshed area is an excellent pool of available labor that is interested in returning to work. They offer a variety of past work experiences to apply to new employment opportunities.

29


HOMEMAKERS Of those who responded as not employed homemakers, 41.9 percent are “very or somewhat likely” to accept employment if the right opportunity is presented. Table 24 shows that the Iowa City Laborshed area is estimated to contain 8,826 homemakers who are willing to work if presented with the right opportunity. This group may represent a quality source of potential available labor in the Laborshed area for certain industries/businesses looking to fill non-traditional work arrangements.

Table 24

Homemakers - Willing to Accept Employment


Zone


Zone*

Estimated Number of Homemakers Willing to Accept by Zone*

Zone 1 63,703 35,564 2,316Zone 2 146,540 71,077 6,003Zone 3 148,669 5,463 507


Respondents willing to accept employment by zone are calculated using a regression model weighted by multiple variables such as education level, gender, age, miles willing to travel, and wages. This model provides an estimate for the total number of individuals “willing to change” by zone. The totals are based on the Total Adjusted Labor Force estimates found in Table 1. For more information regarding homemakers, please contact the Iowa City Area Development Group.

30


RETIRED PERSONS Retired individuals (18-64 years of age) represent an underutilized and knowledgeable pool of workers in some Laborshed areas. In the Iowa City Laborshed area, 19.5 percent of those who are retired are willing to re-enter the workforce at some capacity. Table 25 illustrates that those who are retired and willing to re-enter the workforce reside throughout the survey zones (approximately 3,385).

Table 25

Retired (18 to 64) - Willing to Accept Employment


Zone


Zone*

Estimated Number of Retirees Willing to Accept by Zone*

Zone 1 63,703 35,564 1,281Zone 2 146,540 71,077 1,873Zone 3 148,669 5,463 231


Respondents willing to accept employment by zone are calculated using a regression model weighted by multiple variables such as education level, gender, age, miles willing to travel, and wages. This model provides an estimate for the total number of individuals “willing to change” by zone. The totals are based on the Total Adjusted Labor Force estimates found in Table 1. For more information regarding retirees, please contact the Iowa City Area Development Group.

31


[_

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tu61

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tu30§̈¦380

tu6

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§̈¦74

tu61

§̈¦88

tu63

tu65

tu69

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tu330

§̈¦80

Albia

Tipton

Newton Grinnell

Vinton

Bloomfield

Marshalltown

Marengo

Muscatine

Ottumwa

Toledo

Oskaloosa

Fairfield

Wapello

Washington

Oelwein

Olin

Williamsburg

Waverly

Oxford

De Witt

Hampton

Clinton

Sigourney

Centerville

Pella

Rowley

Delhi

Cascade

Malcom

Ryan

dianola

Hedrick

Zwingle

Grundy Center

Maquoketa

Guttenberg

Marion

Solon

Ollie

Iowa City

AnamosaPalo

Central City

Iowa City

Brighton

Monticello

Manchester

Mediapolis

Wheatland

Edgewood

Ely

Lone Tree

Independence

La Motte

Cedar Falls

Tama

New London

Milton

West Branch

Garrison

Keota

Brooklyn

Walcott

Van Horne

Wellman

Letts

Eldridge

Cantril

Richland

Dubuque

walk

Durant

Swisher

Hopkinton

Packwood

Sherrill

City

Bernard

Donnellson

Eldon

Peosta

Nichols

Belle Plaine

Wilton

Atkins

Victor

Wever

Walker

Kalona

Dysart

Selma

Parnell

Keokuk

Salem

Dyersville

Gilman

Delmar

Bellevue

Kinross

Norway

LiscombOnslow

Janesville

Mount Pleasant

Lowden

Waterloo

Columbus Junction

Burlington

Olds

Keystone

Ainsworth

Colesburg

West Point

Wayland

Fort Madison

Danville

Holy Cross

Earlville

Springville

Long Grove

Calamus

Coralville

Bennett

Martelle

Dundee Greeley

Winfield

Watkins

Mount Vernon

Riverside

Epworth

Fairfax

Brandon

Hartwick

Stockton

Blue Grass

Center Point

Amana

Cincinnati

Stanwood

Moscow

Stockport

Atalissa

Dubuque

Montrose

West Burlington

Yarmouth

Houghton

Princeton

Lockridge

Mechanicsville

Coggon

Saint Paul

Harper

Cedar Rapids

West Liberty

Melbourne

Shellsburg

Deep River

Lost Nation

New Liberty

Morning Sun

Moline

Preston

Durango

Le ClaireBettendorf

Homestead

Wyoming

Dubuque

Baldwin

Alburnett

Crawfordsville

Port Byron

Newhall

North English

West Chester

East MolineDavenport

South English

Worthington

Mount Sterling

Oxford Junction

Center Junction

Denmark

Strawberry Point

Clarence

Elberon

North Liberty

New Vienna

Toddville

Cedar Rapids

Lisbon

Camanche

Conesville

Davenport

Donahue

Davenport

Rock Island

Cedar Rapids

es

Waterloo

Guernsey Iowa City

Webster

Middle Amana

Conroy

Robins

Millersburg

Ladora

nesDes Moines

Middletown

Hills

Clinton

Urbana

Walford

Oakdale

Troy Mills

Hayesville Grandview

Blairstown

Columbus City

Fairfield

GRANTLAFAYETTE GREEN

PUTMAN CLARKSCOTLANDSCHUYLERMERCER

KNOX

HENRY

FULTON

PEORIA

MERCER

WHITESIDE

WARREN

JO DAVIESS

CARROLL

BUREAU

STARK

HANCOCK

ROCK ISLAND

STEPHENSON

HENDERSON

MCDONOUGH

OGLE

LEE

TAZEWELL

MASON

LINN

LEE

TAMA

IOWA

JASPER

JONES

BENTON

DAVIS

CEDAR

CLINTON

HARDIN

STORY

WAYNE

POLK

MARION KEOKUK

SCOTT

JACKSON

LUCAS

JOHNSON

HENRY

DUBUQUE

MAHASKA

GRUNDY

BUTLER

LOUISA

MARSHALL

DELAWAREBUCHANAN

POWESHIEK

MONROE

FRANKLIN

WAPELLO

BLACK HAWK

WARREN

VAN BUREN

WASHINGTON

APPANOOSE

CLAYTON

MUSCATINE

JEFFERSON

BREMER

DES MOINES

FAYETTE

WRIGHT

HAMILTON

CLARKE

DECATUR

Commuter Concentrationby Place of Residence into Iowa City

Area Shown Legend

[_ Iowa City

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County

Missouri County

Wisconsin County

Commuter Concentration

by Place of Residence (per ZIP Code)

1 - 98

99 - 847

848 - 4773

4774 - 7435

10 Mile Intervals Between Rings

0 30 60 90 12015Miles

32


[_

tu61tu151

tu61

tu218

tu30

§̈¦380

tu6

tu20

tu34

§̈¦74

§̈¦80

§̈¦88

tu63tu5 tu163

tu330

§̈¦80

Grinnell, IA Labor Market Area

Ottumwa, IA Labor Market Area

Waterloo, IA MSALabor Market Area

Dubuque, IA MSALabor Market Area

Quad Cities, IA-IL MSALabor Market Area

Burlington, IA Labor Market Area

Fort Madison, IA Labor Market Area

Tipton

Vinton

Marengo

Muscatine

Fairfield

Wapello

Washington

Olin

Williamsburg Oxford

Sigourney

Rowley

Marion

Solon

Iowa City

Mount Pleasant

Palo

Central City

Iowa City

Brighton

Monticello

Ely

Lowden

Lone Tree

West Branch

Garrison

Keota

Brooklyn

Walcott

Van Horne

Wellman

Letts

EldridgeDurant

Swisher

Wayland

Nichols

Belle Plaine

Wilton

Atkins

Victor

Walker

Kalona

Parnell

Salem

Kinross

Springville

Norway

Bennett

Martelle

Winfield

Watkins

Riverside

Fairfax

Stockton

Stanwood

Coggon

Morning Sun

Anamosa

Columbus Junction

Olds

Keystone

Ainsworth

Coralville

Mount Vernon

Blue Grass

Center Point

Amana

MoscowAtalissa

Lockridge

Mechanicsville

Harper

Cedar Rapids

West Liberty

Shellsburg

Deep River

Lost Nation

New Liberty

Le Claire

Bettendorf

Homestead

Wyoming

Alburnett

Crawfordsville

Newhall

North English

West Chester

Davenport

South English

Oxford Junction

Clarence

North Liberty

Toddville

Cedar Rapids

Lisbon

Conesville

Davenport

Donahue

Cedar RapidsCedar Rapids

Iowa City

Webster

Cedar Rapids

Davenport

Middle Amana

Davenport

Conroy

Robins

Millersburg

LadoraSouth Amana

Hills

Iowa City

Urbana

Walford

Cedar Rapids

Fruitland

GrandviewColumbus City

GREENLAFAYETTEGRANT

PUTMAN CLARKSCOTLANDSCHUYLER

KNOX

HENRY

PEORIA

FULTON

BUREAU

MERCER

WHITESIDE

WARREN

LEE

JO DAVIESS

OGLECARROLL

STARK

STEPHENSON

HANCOCK

ROCK ISLAND

HENDERSON

MCDONOUGH TAZEWELL

MASON

MARSHALL

WOODFORD

WINNEBAGO

PUTNAM

LINN

LEE

TAMA

IOWAJASPER

JONES

BENTON

DAVIS

CEDAR

CLINTON

MARION KEOKUK

SCOTT

JACKSON

JOHNSON

HENRY

DUBUQUE

MAHASKA

GRUNDY

LOUISA

HARDIN

MARSHALL

DELAWARE

BUCHANAN

POWESHIEK

MONROE WAPELLO

BLACK HAWK

VAN BUREN

WASHINGTON

APPANOOSEWAYNE

MUSCATINE

BUTLER

JEFFERSON

LUCAS

DES MOINES

STORY

FRANKLIN

CLAYTONBREMER FAYETTE

WARREN

POLK

Labor Market Areas in RegionIowa City Laborshed Area

Area ShownLegend

[_ Iowa City

Iowa City Area Laborshed

Small Labor Market Area (30 Mile Radius)

Large Labor Market Area (50 Mile Radius)

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County

Missouri County

Wisconsin County


0 30 60 90 12015Miles

33


[_

tu61tu151

tu61

tu218

tu30

§̈¦380

tu6

tu20

tu34

§̈¦74

§̈¦80

§̈¦88

tu63

tu63

§̈¦80

Tipton

Vinton

Marengo

Muscatine

Fairfield

Wapello

Washington

Olin

Williamsburg Oxford

Sigourney

Rowley

Marion

Solon

Iowa City

Mount Pleasant

Palo

Central City

Iowa City

Brighton

Monticello

Ely

Lowden

Lone Tree

West Branch

Garrison

Keota

Brooklyn

Walcott

Van Horne

Wellman

Letts

EldridgeDurant

Swisher

Wayland

Nichols

Belle Plaine

Wilton

Atkins

Victor

Walker

Kalona

Parnell

Salem

Kinross

Springville

Norway

Bennett

Martelle

Winfield

Watkins

Riverside

Fairfax

Stockton

Stanwood

Coggon

Morning Sun

Anamosa

Columbus Junction

Olds

Keystone

Ainsworth

Coralville

Mount Vernon

Blue Grass

Center Point

Amana

MoscowAtalissa

Lockridge

Mechanicsville

Harper

Cedar Rapids

West Liberty

Shellsburg

Deep River

Lost Nation

New Liberty

Le Claire

Bettendorf

Homestead

Wyoming

Alburnett

Crawfordsville

Newhall

North English

West Chester

Davenport

South English

Oxford Junction

Clarence

North Liberty

Toddville

Cedar Rapids

Lisbon

Conesville

Davenport

Donahue


Iowa City

Webster

Cedar Rapids

Davenport

Middle Amana

Davenport

Conroy

Robins

Millersburg

LadoraSouth Amana

Hills

Iowa City

Urbana

Walford

Cedar Rapids

Fruitland


GRANT LAFAYETTE GREEN

KNOX

HENRY

MERCER

JO DAVIESS

WARREN

WHITESIDE

CARROLL

ROCK ISLAND

HENDERSON PEORIA

STARK

STEPHENSON

FULTON

BUREAU

LINN

TAMA

IOWA

JONES

BENTON

CEDAR

CLINTON

KEOKUK

SCOTT

JACKSON

JOHNSON

HENRY

MAHASKA

LOUISA

GRUNDY

DAVIS

POWESHIEK

DUBUQUE

WAPELLO

WASHINGTON

LEE

BUCHANAN DELAWARE

MUSCATINE

JEFFERSON

BLACK HAWK

DES MOINES

MONROE

JASPER

VAN BUREN

MARSHALL

APPANOOSE

MARION

BUTLER

Survey Zones by ZIP CodeIowa City Laborshed Area

Area Shown Legend

[_ Iowa City

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County

Wisconsin County



Zone 3 (1 - 110)

Zone 2 (111 - 2,657)

Zone 3 (2,658 - 7,435)


0 25 50 75 10012.5Miles

34


tu61

tu61

tu218

tu30

§̈¦380

tu6

tu20

tu34

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tu330

[_[_

§̈¦80

tu30

tu151

[_Tipton

Grinnell

Vinton

Marengo

Muscatine

Washington

Williamsburg Oxford

De Witt

Sigourney

Montezuma

Malcom

Traer

Marion

Solon

Anamosa

Palo

Central City

Ely

Ga

Chelsea

West Branch

Garrison

Brooklyn

Van Horne

Burlington

Wellman

Winthrop

Keystone

Swisher

Belle Plaine

Atkins

Victor

Walker

Delta

Dysart

Clutier

Dyersville

Norway

Coralville

Watkins

Riverside

Fairfax

Brandon

Hartwick

Center Point

Keswick

Sully

Coggon

Harper

West Liberty

Bussey

Vining

Elberon

Amana

Cedar Rapids

Deep River

Barnes City

Homestead

Baldwin

Newhall

North EnglishLynnville

Clarence

North Liberty

Toddville

Cedar Rapids

Davenport

Cedar Rapids

Guernsey

Cedar Rapids

Webster

Cedar Rapids

Davenport

Middle Amana

ConroyLadora

Tiffin

Urbana

Walford

Cedar Rapids

Troy Mills

Blairstown

South Amana

GRANT

MERCER

WARREN

ROCK ISLAND

JO DAVIESS

HENDERSON

HENRY

KNOX

JASPER

JONES

MARION

SCOTT

DUBUQUE

JACKSON

MAHASKA

CLINTON

GRUNDY

LOUISA

HARDIN

DELAWARE

HENRYMONROE

BLACK HAWK

WAPELLOLUCAS

BUTLER

DES MOINES

STORY

FRANKLIN

TAMA

MARSHALL

BUCHANAN

MUSCATINE

JEFFERSON

BREMER

WARREN

CLAYTON

POLK

Commuter Concentrationby Place of Residence into the Amanas

Area Shown Legend

[_ The Amanas

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County

Wisconsin County



1 - 16

17 - 52

53 - 121

122 - 338


0 20 40 60 8010Miles

35


[_

tu151

tu61tu218

§̈¦380

tu6

tu20

tu63

tu

tu5tu163

tu330

§̈¦80

tu330

Grinnell

Vinton

Marengo

Toledo

Williamsburg

Montezuma

Traer

Marion

La Porte City

Waterloo

ChelseaTama

Garrison

Brooklyn

Van HorneKeystone

Peosta

Belle Plaine

Victor

Dysart

Clutier

Norway Fairfax

Hartwick

Amana

Elberon

North Liberty

Iowa City

Ladora

Hiawatha

Urbana

BlairstownLuzerne

GRANT

MERCER

ROCK ISLAND

LINNTAMA

IOWAJASPER

JONES

BENTON

CEDAR

HARDIN

MARION KEOKUK

JOHNSON

MAHASKA

GRUNDY

LOUISA

DUBUQUE

MARSHALL

DELAWAREBUCHANAN

POWESHIEK

BLACK HAWK

WASHINGTON

STORY

MUSCATINE

BUTLER

POLK

FRANKLIN

CLINTON

SCOTT

JACKSON

WARREN

HENRYLUCAS MONROE WAPELLO

BREMER CLAYTON

JEFFERSON

FAYETTE

Commuter Concentrationby Place of Residence into Belle Plaine

Area Shown Legend

[_ Belle Plaine

Interstate

4-Lane Highway

US Highways

State Highways

Iowa County

Illinois County

Wisconsin County



1 - 4

5 - 12

13 - 22

23 - 281


0 20 40 60 8010Miles

36


[_

tu61tu151

tu61

tu218

tu30

§̈¦380

tu6

tu20

tu34

§̈¦74

§̈¦88

tu63

tu163

tu330

§̈¦80

Tipton

Vinton

Marengo

Muscatine

OttumwaFairfield

Washington

Oelwein

Olin

Williamsburg Oxford

Cascade

Marion

Solon

Waterloo

Iowa City

Jesup

Mount Pleasant

Anamosa

Palo

Iowa City

Monticello

Manchester

Wheatland

La Porte City

Ely

Lone Tree

Cedar Falls

West Branch

Keota

Brooklyn

Wellman

Hudson

Letts

Richland

Durant

Swisher

Nichols

Belle Plaine

Atkins

Victor

Walker

Kalona

Parnell

Norway

Winfield

Riverside

Columbus Junction

Burlington

Olds

Ainsworth

Wayland

Coralville

Mount VernonFairfax

Amana

Stanwood

Atalissa

MechanicsvilleCedar Rapids

West LibertyDeep River

Homestead

Newhall

North English

West Chester

Davenport

Clarence

North Liberty

Cedar Rapids

Lisbon

Conesville

Davenport

Cedar Rapids

Iowa City

Webster

Cedar Rapids

Middle Amana

Davenport

Conroy

Robins

Ladora

Hills

Walford

Oakdale

Columbus City

Tiffin

Hiawatha

LAFAYETTEGRANT GREEN

KNOX

HENRY

MERCER

WARREN

JO DAVIESS

WHITESIDE

CARROLL

ROCK ISLAND

HENDERSON PEORIA

STARK

FULTON

STEPHENSON

BUREAU

LINNTAMA

IOWA

JONES

BENTON

CEDAR

CLINTON

JASPER

KEOKUK

SCOTT

JACKSON

JOHNSON

HENRY

DUBUQUE

LEE

MAHASKA

DAVIS

GRUNDY

LOUISA

MARION

MARSHALL

DELAWAREBUCHANAN

POWESHIEK

MONROE WAPELLO

BLACK HAWK

WASHINGTON

MUSCATINE

JEFFERSON

HARDIN

DES MOINES

BUTLER

VAN BURENAPPANOOSE

LUCAS

CLAYTONBREMERFAYETTE

WAYNE

FRANKLIN

Commuter Concentrationby Place of Residence into Coralville

Area Shown Legend

[_ Coralville

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County

Wisconsin County



1 - 35

36 - 165

166 - 319

320 - 813


0 20 40 60 8010Miles

37


[_

tu61

tu151

tu61

tu218

tu30§̈¦380

tu6

tu34

tu63

§̈¦80

Tipton

Washington

Williamsburg

Solon

Iowa City

Iowa City

Brighton

Lone Tree

New London

West Branch

Columbus Junction

Wellman

Ainsworth

Swisher

NicholsKalona

Parnell

Coralville

Mount Vernon

Riverside

StanwoodMechanicsville

West LibertyNorth English

South English

North Liberty


Iowa City

Webster

Cedar Rapids

Hills

Tiffin

Walford

MERCER

WARREN

ROCK ISLAND

KNOX

HENDERSON

HENRY

JO DAVIESS

CARROLL

LINNTAMA

IOWA

CEDAR

BENTON

JONES

KEOKUK

SCOTT

CLINTON

JOHNSON

HENRY

LOUISA

MAHASKA

POWESHIEK

JACKSON

WAPELLO

WASHINGTON

MUSCATINE

JEFFERSON

DAVIS

DES MOINES

MONROE

VAN BUREN

LEE

APPANOOSE

JASPER

MARSHALL

GRUNDY

Commuter Concentrationby Place of Residence into Hills

Area Shown Legend

[_ Hills

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County



1 - 4

5 - 11

12 - 22

23 - 31


0 20 40 60 8010Miles

38


[_

tu61

tu151

tu61tu218

tu30

§̈¦380

tu6

tu34

tu63

tu163

§̈¦80

§̈¦74

Muscatine

Washington

Williamsburg

Sigourney

Ollie

Iowa City

Mount Pleasant

Iowa City

Brighton

Lone Tree

West Branch

KeotaColumbus Junction

Wellman

Ainsworth

Wayland

Belle Plaine

Walker

Kalona

Parnell

Coralville

Riverside

Amana

Fort Madison

Cedar Rapids

Homestead

North English

West Chester

South English

North Liberty

Cedar Rapids

Iowa City

Hills

Tiffin

Urbana

Walford

Columbus City

MERCER

WARREN

KNOX

HENDERSON

ROCK ISLAND

HENRY

FULTON

JO DAVIESS

CARROLL

MCDONOUGH

LINNTAMA

IOWA

CEDAR

BENTON

LEE

JONES

CLINTON

KEOKUK

SCOTT

DAVIS

JOHNSON

HENRY

MAHASKA

LOUISA

JACKSON

POWESHIEK

WAPELLO

JASPER

MONROE

WASHINGTON

MUSCATINE

JEFFERSON

VAN BUREN

DES MOINES

MARSHALL

APPANOOSE

MARION

GRUNDYHARDIN

Commuter Concentrationby Place of Residence into Kalona

Area Shown Legend

[_ Kalona

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County



1 - 7

8 - 22

23 - 70

71 - 314


0 20 40 60 8010Miles

39


[_

tu61

tu151

tu61

tu218

tu30

§̈¦380

tu6

tu20

tu34

§̈¦88

tu63

tu163

§̈¦80

§̈¦74

Tipton

Vinton

Marengo

Muscatine

Washington

Williamsburg Oxford

Ryan

Marion

Solon

Iowa City

Anamosa

Palo

Central City

Iowa City

Monticello

Manchester

Ely

Lone Tree

New Sharon

West Branch

KeotaColumbus Junction

Wellman

Keystone

Farley

Ainsworth

Swisher

Hopkinton

Colesburg

Nichols

Belle Plaine

Wilton

Atkins

Victor

Walker

Kalona

Parnell

Delmar

Earlville

Springville

Coralville

Bennett

Martelle

Riverside

Fairfax

Amana

Stanwood

Keswick

Mechanicsville

West Liberty

Shellsburg

Davenport

Mount Vernon

Center Point

Cedar Rapids

Lost Nation

Bettendorf

Homestead

Dubuque

Alburnett

Newhall

North English

South English

Clarence

North Liberty

Toddville

Cedar Rapids

Lisbon

Conesville

Monmouth


Iowa City

Webster

Cedar Rapids

Middle Amana

Robins

South Amana

Hills

Tiffin

Iowa City

Urbana

Walford

Troy Mills

Blairstown

Davenport

GRANT LAFAYETTE

MERCER

HENRY

KNOX

JO DAVIESS

ROCK ISLAND

WARREN

WHITESIDE

CARROLL

HENDERSON

LINNTAMA

IOWA

JONESBENTON

CEDAR

CLINTON

KEOKUK

SCOTT

JACKSON

JOHNSON

DUBUQUE

MAHASKA

GRUNDY

LOUISA

DELAWAREBUCHANAN

POWESHIEKJASPER

BLACK HAWK

WASHINGTON

HENRYWAPELLO

MUSCATINE

MONROE JEFFERSON

MARSHALL

BUTLER

MARION

DES MOINES

BREMER FAYETTE

HARDIN

FRANKLIN

Commuter Concentrationby Place of Residence into North Liberty

Area Shown Legend

[_ North Liberty

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County

Wisconsin County



1 - 10

11 - 31

32 - 71

72 - 354


0 25 50 75 10012.5Miles

40


[_

tu61

tu151

tu61tu218

§̈¦380

tu6

tu

tu63

§̈¦80

tu30

Marengo

WilliamsburgOxford

Solon

Iowa City

Kalona

Coralville

Stanwood

Homestead

North Liberty

Cedar Rapids

Iowa City

South Amana

Hills

Tiffin

MERCER

ROCK ISLAND

WARRENHENDERSON

LINNTAMA

IOWA

JONES

BENTON

CEDAR

KEOKUK

JOHNSON

LOUISA

MAHASKA

POWESHIEK

WASHINGTON

MUSCATINE

SCOTT

CLINTON

JACKSON

HENRYWAPELLO JEFFERSONMONROE

DES MOINES

GRUNDY BLACK HAWK BUCHANAN DELAWARE

JASPER

MARSHALL

DUBUQUE

Commuter Concentrationby Place of Residence into Oxford

Area Shown Legend

[_ Oxford

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County



1 - 2

3 - 4

5 - 32


0 20 40 60 8010Miles

41


[_

tu61

tu151

tu61

tu218

tu30

§̈¦380

tu6

tu20

tu34

§̈¦88

tu63

§̈¦80

§̈¦74

tu20

Tipton

Vinton

Marion

Solon

Iowa City

Iowa City

Ely

West Branch

Burlington

Ainsworth

Swisher

Nichols

Coralville

Mount Vernon

StanwoodMechanicsvilleCedar Rapids

New Liberty

North Liberty

Cedar Rapids

Lisbon

Cedar Rapids

Iowa City

Cedar Rapids

Walford

KNOX

HENRY

MERCER

JO DAVIESS

WARREN

ROCK ISLAND

WHITESIDE

CARROLL

HENDERSON

LINNTAMA

IOWA

JONES

BENTON

CEDAR

CLINTON

KEOKUK

SCOTT

JACKSON

JOHNSON

HENRY

LOUISA

MAHASKA

POWESHIEK

WAPELLO

WASHINGTON

MUSCATINE

DUBUQUE

JEFFERSON

BUCHANAN DELAWAREBLACK HAWK

DES MOINES

GRUNDY

MONROE

DAVIS VAN BURENAPPANOOSE

JASPER

MARSHALL

Commuter Concentrationby Place of Residence into Solon

Area Shown Legend

[_ Solon

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County



1 - 2

3 - 4

5 - 11

12 - 99


0 20 40 60 8010Miles

42


[_

tu

tu151

tu61

§̈¦380

tu6

tu63

§̈¦80

tu30

tu20

Vinton

Marengo

Marion

Solon

Anamosa

Central City

Iowa City

Ely

Swisher

Hopkinton

Atkins

Norway

Coralville

Martelle

Mount Vernon

FairfaxCedar Rapids

North Liberty

Cedar Rapids

Cedar Rapids

Cedar Rapids

Iowa City

ROCK ISLAND

LINN

IOWA

TAMA

JONES

BENTON

CEDAR

JOHNSON

POWESHIEK

MUSCATINE

DUBUQUEBUCHANAN DELAWAREBLACK HAWK

KEOKUK

SCOTT

CLINTON

JACKSON

WASHINGTONMAHASKA

GRUNDY

LOUISA

Commuter Concentrationby Place of Residence into Swisher

Area Shown [_ Swisher

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County



1 - 3

4 - 10

11 - 30


0 10 20 30 405Miles

43


[_

tu

tu151

tu61

tu218

§̈¦380

tu6

tu63

tu63

§̈¦80

tu30

Muscatine

Oskaloosa

Oxford

Iowa City

Ely

Wellman

Ainsworth

Swisher

Kalona

Coralville

Harper

Homestead

Conesville

Cedar Rapids

Iowa City

Tiffin

MERCER

ROCK ISLAND

LINNTAMA

IOWA

JONES

BENTON

CEDAR

KEOKUK

JOHNSON

MAHASKA

LOUISA

POWESHIEK

WASHINGTON

MUSCATINE

JASPER

GRUNDY

MARSHALL

SCOTT

CLINTON

BUCHANAN

JACKSON

DUBUQUEDELAWAREBLACK HAWK

MARION

HENRYWAPELLO JEFFERSONMONROE

Commuter Concentrationby Place of Residence into Tiffin

Area Shown Legend

[_ Tiffin

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County



1 - 2

3 - 5

6 - 21


0 20 40 60 8010Miles

44


[_

tu61

tu151

tu61

tu218

tu30§̈¦380

tu6

tu20

tu34

§̈¦74

u

§̈¦88

tu63

tu163

tu0

§̈¦80

TiptonMarengo

Muscatine

Fairfield

Olin

Williamsburg Oxford

Clinton

Montezuma

Marion

Solon

Iowa City

Mount Pleasant

Iowa City

Fulton

Manchester

Lowden

Waterloo

Lone Tree

West Branch

Keota

Swisher

Wayland

Nichols

Wilton

Kalona

Salem

Riverside

Columbus Junction

Burlington

West Point

Coralville

Center Point

Stanwood

MoscowAtalissa

Mechanicsville

Saint Paul

Cedar Rapids

West Liberty

New Liberty

North English

Davenport

y

Clarence

North Liberty

Toddville

Cedar Rapids

Lisbon

Davenport

Rock Island


Iowa City

Cedar Rapids

DavenportDavenport

Robins

Hills

Blairstown

LAFAYETTEGRANT GREEN

KNOX

HENRY

MERCER

WARREN

WHITESIDE

JO DAVIESS

CARROLL

PEORIA

ROCK ISLAND

STARK

HENDERSON

BUREAU

STEPHENSON

FULTON

OGLE

LINNTAMA

IOWA

JONES

BENTON

CEDAR

CLINTON

LEE

KEOKUK

SCOTT

JACKSON

DAVIS

JOHNSON

HENRY

DUBUQUE

JASPER

MAHASKA

GRUNDY

LOUISA

DELAWAREBUCHANAN

POWESHIEK

MONROE WAPELLO

BLACK HAWK

MARSHALL

WASHINGTONMARION

MUSCATINE

JEFFERSON

VAN BUREN

DES MOINES

APPANOOSE

BUTLER

HARDIN

BREMER CLAYTONFAYETTE

FRANKLIN

LUCAS

WAYNE

Commuter Concentrationby Place of Residence into West Branch

Area Shown Legend

[_ West Branch

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County



1 - 4

5 - 12

13 - 25

26 - 226


0 20 40 60 8010Miles

45


[_

tu61

tu151

tu61tu218

tu30

§̈¦380

tu6

tu20

tu34

§̈¦74

§̈¦88

tu63

§̈¦80

Tipton

Grinnell

Marengo

Muscatine

Toledo

Washington

Williamsburg

Milana

Maquoketa

Marion

Solon

Ollie

Iowa City

Mount Pleasant

Iowa City

Brighton

Monticello

Mediapolis

Monmouth

Wheatland

Illinois City

New Boston

Ely

Lowden

Lone Tree

Independence

West Branch

Keota

Brooklyn

Walcott

Wellman

Letts

Durant

Nichols

Wilton

Kalona

Parnell

Bennett

Riverside

Fairfax

Stockton

Stanwood

Keswick

Columbus Junction

Ainsworth

Coralville

Mount Vernon

Moscow

Atalissa

MechanicsvilleCedar Rapids

West Liberty

Moline

Bettendorf

Alburnett

East Moline

Davenport

Clarence

North Liberty

Cedar Rapids

Conesville

SilvisDavenportRock Island

Cedar Rapids

Iowa City

Cedar Rapids

DavenportDavenportHills

Iowa City

Walford

Fruitland

Montpelier


KNOX

HENRY

MERCER

WARREN

JO DAVIESS

WHITESIDE

CARROLL

ROCK ISLAND

HENDERSONPEORIA

STARK

FULTON

STEPHENSON

BUREAU

LINNTAMA

IOWA

JONESBENTON

CEDAR

CLINTON

KEOKUK

SCOTT

JACKSON

JOHNSON

HENRY

MAHASKA

LOUISA

DAVIS

LEE

POWESHIEK

WAPELLO

WASHINGTON

MUSCATINE

GRUNDY

DUBUQUE

JEFFERSON

DES MOINES

BUCHANAN DELAWARE

VAN BUREN

MONROE

BLACK HAWK

JASPER

APPANOOSE

MARSHALL

MARION

Commuter Concentrationby Place of Residence into West Liberty

Area Shown Legend

[_ West Liberty

Interstate

4-Lane Highway

US Highways

State Highways

Illinois County

Iowa County



1 - 17

18 - 66

67 - 214

215 - 549


0 25 50 75 10012.5Miles

46


47


EXHIBITS

48


Exhibit A

49


BACKGROUND INFORMATION In early 1998, the Institute for Decision Making (IDM) at the University of Northern Iowa (UNI) completed the first pilot Laborshed study. The Laborshed approach and methodology was developed to meet the specific needs of economic development groups trying to understand and detail the unique characteristics of their area labor force. From 1998 to June, 2001, IDM completed 24 Laborshed studies for Iowa communities and gained national attention for its innovative approach. Beginning in 1999, Laborshed studies were completed in partnership with the Iowa Department of Economic Development (IDED) and Iowa Workforce Development (IWD) for communities that met specific criteria and for “immediate opportunities” (expansion projects or prospects). During the 2000 legislative session, the General Assembly mandated that as of July 1, 2001, IWD assume the responsibilities for conducting Laborshed studies for Iowa communities. IDM staff worked with members of IWD to train them in IDM’s Laborshed process and methodology. Beginning in July, 2001, IWD assumed all responsibilities for scheduling and conducting all future Laborshed projects in Iowa. The availability of a well-trained and educated labor force is among the top three important location factors for businesses considering expansions or relocations (Area Development, December 2000). Previously faced with historically low unemployment rates, local economic development officials throughout Iowa needed access to obtain timely and tailored data to help define their available labor force and its characteristics. Iowa’s low rates of unemployment often lead to the incorrect assumption that economic growth cannot occur within the state. It was presumed that employers will be unable to attract employees from Iowa communities because the areas have reached full employment. Even in today’s economy, employers desire a higher skilled and/or educated worker. Employers also do not have the excess resources to blanket an area for employment opportunity recruitment. The Laborshed study addresses both of these issues and more to assist employers and communities with expansion efforts.

Contrary to these assumptions, many companies currently expanding or locating in Iowa are receiving between five and ten applicants for each new position that they have open. The discrepancy between the assumptions and the reality of these measurements indicates that a problem exists in the way unemployment data is defined, measured, reported and used. When unemployment statistics are utilized as the sole method for determining labor availability, they appear to lead to inaccurate conclusions regarding the potential available labor supply within a “Laborshed” or sub-labor market area (sub-LMA). A Laborshed is defined as the actual area or nodal region from which an area draws its commuting workers. This region has been found to extend beyond the confines of county and state boundaries typically used to delineate labor information. The limitations of current labor data have significant implications for local economic development officials as they strive to create additional jobs and enhance wealth within their region.

Exhibit B

50


SURVEY METHODOLOGY AND DATA Understanding what Iowa employment and unemployment figures represent requires a familiarity with how estimates are calculated and how data differs at the national, state and sub-state levels. The U.S. Department of Labor’s Bureau of Labor Statistics (BLS) calculates employment statistics for the nation, while state-level data is computed independently by each state. Unfortunately, the methodology used by the BLS is such that the data cannot be directly translated into comparable state data. Exhibit C reviews the methodology currently in place.

In order to obtain current and accurate labor force information for the Laborshed area, NCS Pearson administered a random household telephone survey to individuals residing within the Laborshed boundaries during August 2010. The survey was designed by IDM with assistance from the Center for Social and Behavioral Research at UNI. The overall goal of the process, to collect a minimum of 600 valid phone surveys completed by respondents 18 to 64 years of age, was achieved. Validity of survey results is estimated at a confidence of +/- 5 percent of the 600 responses analyzed in this report.

To ensure that an even distribution of respondents is achieved, an equal number of calls are completed to three separate survey zones (see Survey Zones by ZIP Code – Iowa City Laborshed area map). The three zones created are classified as Zone 1) Iowa City, Zone 2) ZIP codes adjacent or near Zone 1 that have a moderate number of residents working in Iowa City and Zone 3) the ZIP codes in outlying areas with a low concentration of residents working in Iowa City. This distribution of surveys is an attempt to avoid a clustering of respondents in Iowa City or in the surrounding rural areas. Utilizing this survey distribution method also provides the basis for comparisons among the zones and offers a more valid means of applying the survey results within each individual zone.

Survey administrators posed questions to determine the respondents’ gender, age, education level, place of residence and current employment status. Employed respondents also identified the location of their employer, employer type, occupation, years of employment in their occupation, employment status, current salary or wage, additional education/skills possessed, number of jobs currently held, distance traveled to work and the hours worked per week. Employed respondents were then asked how likely they were to change employers or employment, how far they would be willing to travel for employment, the wage required for them to change employment and the benefits desired for new employment. Underemployment was estimated by examining those employees desiring more hours of work than offered in their current position, those who stated they possessed additional education/skills that they do not utilize in their current position and wages insufficient enough to keep them above the poverty level.

Respondents in the 18-64 year age range self-identifying themselves as unemployed, homemakers/not employed or retired were asked a series of questions to determine what job characteristics and benefits were most important to them when considering employment, the reasons for unemployment, obstacles to employment and how far they would be willing to travel to accept employment. Information on previous employers and skills was also gathered for these sectors.

Once completed, the results of the survey were compiled and cross-tabulated to determine the relationship between the variables in each zone and the entire survey sample. Documenting and analyzing the Laborshed survey results by zone and by characteristics, provides new insight into the labor force that is currently unavailable in any other form.

Exhibit C

51


CURRENT METHODS OF ESTIMATING EMPLOYMENT AND UNEMPLOYMENT

The federal government and the state of Iowa estimate an area’s labor force by drawing from the portion of the civilian population that is non-institutionalized, 16 years of age or older and currently employed or unemployed (BLS Handbook, Chapter 1, p. 5). The BLS defines employed persons in the following two ways:

1. Did any work as paid employees, for their own business, profession, on their own farm, or worked 15 hours or more as unpaid workers in a family-operated enterprise (BLS Handbook, Chapter 1, p. 5).

2. Did not work but had jobs or businesses from which they were temporarily absent

due to illness, bad weather, vacation, child-care problems, labor dispute, maternity or paternity leave, or other family or personal obligations -- whether or not they were paid by their employers for the time off and whether or not they are seeking other jobs. Individuals volunteering or engaged in housework, painting and home repair around their own residence are not considered employed (BLS Handbook, Chapter 1, p. 5).

Unemployed persons are defined as those individuals that were not employed on a given reference week prior to questioning and who made an effort to find work by contacting prospective employers. These individuals identified that they are ready to work with the exception of inability due to a temporary illness. Individuals are also classified as unemployed if they have been laid off and are awaiting recall back to their positions (BLS Handbook, Chapter 1, p. 5). The unemployed are grouped into job losers (both temporarily and permanently laid off), quit/terminated and looking for work, re-entrants to the job market after an extended absence and new entrants that have never worked (BLS Handbook, Chapter 1, p. 5). Those individuals that are not classified as employed or unemployed are not considered to be part of the labor force by BLS. The non-working designation may be due to a variety of reasons; however, the underlying factor is that the individuals have not sought employment within the past four weeks (BLS Handbook, Chapter 1, p. 6). Because the BLS utilizes a multiple step process to estimate employment and underemployment statistics on a monthly basis, this process cannot be described in only a few paragraphs. A complete summary of the process used to generate national estimates and an outline of the process used to generate state and sub-state projections is available through IWD.

Exhibit C

52


METHODS FOR ESTIMATING EMPLOYMENT The BLS uses the employed and unemployed persons to calculate the civilian labor force, the unemployment rate and labor force participation rate. The labor force is: employed + unemployed = labor force The labor force participation rate is: labor force / non-institutionalized citizens 16+ years of age = LFPR The unemployment rate is the percentage of the civilian labor force that is unemployed: unemployed / total labor force = unemployment rate (BLS Handbook,

Chapter 1, p. 5) A proper interpretation of the unemployment rate requires an understanding of the processes used to generate the data on which the calculations are based. The BLS uses the monthly Current Population Survey (CPS) to collect data from a sample of 59,000 households, taken from 754 sample areas located throughout the country. The purpose of the survey is to collect information on earnings, employment, hours of work, occupation, demographics, industry and socio-economic class. The data is obtained through personal and telephone interviews. Of the 59,000 households, only about 50,000 are generally available for testing due to absence and illness. The 50,000 households generate information on 94,000 individuals (BLS Handbook, Chapter 1, p. 8). Each household is interviewed for two, four-month periods, with an eight-month break between the periods. The pool of respondents is divided into 8 panels, with a new panel being rotated each month (BLS Handbook, Chapter 1, p. 10). The 754 sample areas from which the households are selected represent 3,141 counties and cities broken into 2,007 population sample units (PSU’s). A PSU can consist of a combination of counties, urban and rural areas, or entire metropolitan areas that are contained within a single state. The PSU’s for each state are categorized into the 754 sample groups of similar population, households, average wages and industry. The 754 sample areas consist of 428 PSU’s that are large and diverse enough to be considered an independent PSU and 326 groupings of PSU’s (BLS Handbook, Chapter 1, p. 9). The sample calculates an unemployment estimate with a 1.9 percent coefficient of co-variation. This is the standard error of the estimate divided by the estimate, expressed as a percentage. This translates into a .2-percent change in unemployment being significant at the 90 percent confidence level. The respondent’s information is weighted to represent the group’s population, age, race, sex and the state from which it originates. Using a composite estimation procedure minimizes the standard of error for the estimate. This estimate is based on the two-stage rotation estimate on data obtained from the entire sample for the current month and the composite estimate for the previous month, adjusted by an estimate of the month-to-month change based on the six rotation groups common to both months (BLS Handbook, Chapter 1, p. 8). The estimates are also seasonally adjusted to minimize the influence of trends in seasonal employment.

IOWA & SUB-STATE UNEMPLOYMENT RATES

The CPS produces reliable national unemployment estimates; however these do not translate into estimates for all state and sub-state areas. Only 11 of the most populous states and the LMA’s of Los Angeles and New York City are large enough to be calculated by the CPS. The unemployment estimates for the 39 other states, 5600 geographic areas, LMA’s, counties and cities, are calculated using BLS guidelines established by each state’s employment agency.

Exhibit C

53


The state of Iowa’s counties are each considered small LMA’s, with the exception of micropolitan and metropolitan statistical areas. For further definition of counties included in micropolitan statistical areas, visit www.iowaworkforce.org/lmi/pressrelease/iowamicro.pdf and for counties included in metropolitan statistical areas, visit www.iowaworkforce.org/lmi/pressrelease/iowamsa.pdf. A time series model is used to estimate state labor force statistics and a Handbook method is used for sub-state projections. The state unemployment estimates are based on a time series to reduce the high variability found in the CPU estimates caused by small sample size. The time series combines historical relationships in the monthly CPS estimates along with Unemployment Insurance and Current Employment Statistics (CES) data. Each State has two models designed for it that measure the employment to work ratio and the unemployment rate (BLS Handbook, Chapter 4, p. 37). The CES is a monthly survey of employers conducted by the BLS and state employment agencies. Employment, hours/overtime and earning information for 400,000 workers are obtained from employer payroll records. Annually, the monthly unemployment estimates are benchmarked to the CPS estimate so that the annual average of the final benchmarked series equals the annual average and to preserve the pattern of the model series (BLS Handbook, Chapter 4, p. 38). The sub-state unemployment estimates are calculated by using the BLS Handbook Method. The Handbook Method accounts for the previous status of the unemployed worker and divides the workers into two categories: those who were last employed in industries covered by State Unemployment Insurance (UI) laws and workers who either entered the labor force for the first time or reentered after a period of separation (BLS Handbook, Chapter 4, p. 38). Individuals considered covered by UI are those currently collecting UI benefits and those that have exhausted their benefits. The data for those that are insured is collected from State UI, Federal and Railroad programs. The estimate for those who have exhausted their funds is based on the number who stopped receiving benefits at that time and an estimate of the individuals who remain unemployed (BLS Handbook, Chapter 4, p. 39). New entrants and reentrants into the labor force are estimated based on the national historical relationship of entrants to the experienced unemployed and the experienced labor force. The Department of Labor states that the Handbook estimate of entrants into the labor force is a function of (1) the month of the year, (2) the level of the experienced unemployed, (3) the level of the experienced labor force and (4) the proportion of the working age population (BLS Handbook, Chapter 4, p. 39). The total entrants are estimated by: ENT = A(X+E)+BX where: ENT = total entrant unemployment E = total employment X = total experienced unemployment A,B = synthetic factors incorporating both seasonal variations and the assumed relationship between the proportion of youth in the working-age population and the historical relationship of entrants, either the experienced unemployed or the experienced labor force (BLS Handbook, Chapter 4, p. 39).

Exhibit C

54


Total employment (E) estimates represent the total number of paid employees in non-farm industries. The estimates are based on various sources, including the CES survey and state designed surveys of establishments. These figures are combined with a weighted factor accounting for historic employment relationships found in the Census. The resulting estimate is combined with standard estimates for agricultural workers, non-farm self-employed and unpaid family workers and private household workers to compute the total Handbook employment (BLS Handbook, Chapter 4, p. 39). Total unemployment for the sub-state/LMA is estimated by the formula: Ua(t) = Us(t) * UHBa(t) where: U = total unemployment UHB = Handbook unemployment a = area s = State t = time As with the state data, the sub-state/LMA estimates are benchmarked annually so that they sum to the revised state estimates of employment and unemployment (BLS Handbook, Chapter 4, p. 39). Unemployment estimates for portions of the LMAs are calculated by one of two methods, (1) the population-claims method, or (2) the Census-share method. The population-claims method is the preferred method according to the BLS. Where available, resident based UI claims data for the sub-LMA area are used to find the ratio of the claims to the total number of UI claims within the LMA. This figure is used to analyze the estimate of experienced unemployed in the area. The number of unemployed entrants is based on the Census distribution of adult and teenage population groups. The employment is estimated using current population distributions prepared by the Census Bureau and weighted by each area’s Census relative share of employment to population. The Census-share method is used if UI claims data for the sub-LMA area is unavailable. Instead, the decennial Census data from the county in which the area is located is divided into a portion consistent with the size of the area. The Census-share method is less accurate than the population-claims method (BLS Handbook, Chapter 4, p. 40). LIMITATIONS

Since the State, LMA & sub-LMA data are not directly obtained from a survey; the estimates calculated are subject to a level of error. These errors can occur due to improper estimations and insufficient data sources. Unfortunately, a universal level of error cannot be easily computed because of the wide variety of sources and methods used. The CPS information used to calculate the national estimates and to benchmark the state figures is subject to sampling and non-sampling error. Non-sampling errors in the CPS, such as those due to respondent bias and question interpretation, are minimized through re-interviewing respondents and rotating the panels of respondents. Sampling errors in the CPS over time show that 68 percent of the intervals are within 1 standard deviation, 90 percent are within 1.6 standard deviations and 95 percent of the intervals are within 2 standard deviations of the mean (BLS Handbook, Chapter 1, p. 14).

Exhibit D

55


OCCUPATIONAL EMPLOYMENT STATISTICS (OES) CATEGORY STRUCTURE

Managerial/Administrative Occupations Professional, Paraprofessional, & Technical Occupations

Engineers Natural Scientists Computer, Mathematical, and Operations Research Social Scientists Teachers Health Practitioners Writers, Artists, Entertainers, and Athletes

Sales Occupations Clerical/Administrative Support Occupations

Secretarial Electronic Data Processing

Service Occupations Protective Service Food and Beverage Health Service Cleaning and Building Service Personal Service

Agricultural Occupations Production, Construction, Operating, Maintenance, & Material Handling Occupations

Construction Trades and Extraction Precision Production Machine Setters, Set-Up Operators, Operators, and Tenders Hand Working Occupations Plant and System Transportation and Material Moving Helpers, Laborers, and Material Movers, Hand

56


LABOR MARKET INFORMATION (EMPLOYER-BASED) WEB RESOURCES:

Iowa Wage Survey http://www.iowaworkforce.org/lmi/occupations/wages/index.htm Affirmative Action http://www.iowaworkforce.org/lmi/publications/affirm/ Condition of Employment http://www.iowaworkforce.org/lmi/condempl.pdf Covered Employment & Wages by Counties http://www.iowaworkforce.org/lmi/empstat/coveredemp.html Iowa Job Outlook Statewide http://www.iowaworkforce.org/lmi/outlook/index.html Iowa Licensed Occupations http://www.iowaworkforce.org/lmi/publications/licocc/ Iowa Workforce Development Trends http://www.iowaworkforce.org/trends Iowa Works – Iowa Workforce Development’s Portal for Iowa Businesses http://www.iowaworks.org Labor Force Summaries http://www.iowaworkforce.org/lmi/laborforce/index.html Labor Market Information Directory http://www.iowaworkforce.org/lmi/lmidirectory Occupational Projections & Job Outlooks http://www.iowaworkforce.org/lmi/occupations/index.html

57


REFERENCES Breslow, Marc & Howard, Matthew. “The Real Underemployment Rate,” Monthly Labor Review May/June (1995): 35.

Canup, Dr. C.R. (Buzz), President. “Ranked #3, Availability of Skilled Labor.” AreaDevelopment (April/May 2006). CensusCD+Maps (Version 2.0) [CD-ROM]. (2000). East Brunswick, NJ: GeoLytics, Inc. [Producer and Distributor].

Clogg, Clifford D. Measuring Underemployment. New York: Academic Press, 1979.

Ecker, Dr. Mark (2001). “Estimating the Potential Workforce for Iowa Laborsheds.” Institute for Decision Making, University of Northern Iowa.

Fleisher, Belton M. & Knieser, Thomas J. (1984). Labor Economics: Theory, Evidence and Policy, Third Edition. Englewood Cliffs: Prentice-Hall.

GeoSystems Global Corporation. (1999). MapQuest [On-line]. Available: www.mapquest.com.

Glass, Robert H., Krider, Charles E., & Nelson, Kevin. (1996). “The Effective Labor Force in Kansas: Employment, Unemployment and Underemployment.” The University of Kansas Institute of Public Policy and Business Research, School of Business, Department of Economics, Research Papers. Report No. 227, January 1996.

Hedgcoth, Rachael, Senior Editor. “America’s 50 Hottest Cities for Manufacturing Expansions and Relocations.” Expansion Management (January 2003).

How the Government Measures Unemployment, Report 864, Bureau of Labor Statistics, U.S. Department of Labor, February 1994.

Kahn, Linda J., & Morrow, Paula C. “Objective and Subjective Underemployment Relationships to Job Satisfaction.” Journal of Business Research 22(1991): 211-218.

Leys, Tony. “A Lot of Job-Seekers Are Already Working,” The Des Moines Register, July 28, 1996.

“Labor Force Data Derived from the Current Population Survey,” BLS Handbook of Methods, Chapter 1, Bureau of Labor Statistics, U.S. Department of Labor, April 1997.

“Measurement of Unemployment in States and Local Areas,” BLS Handbook of Methods, Chapter 4, Bureau of Labor Statistics, U.S. Department of Labor, April 1997.

Method for Obtaining Local Area Unemployment Estimates, Iowa Workforce Development.

Rand McNally. (2001). Rand McNally [On-line]. Available: www.randmcnally.com.

Tolbert, Charles M., & Killian, Molly S. “Labor Market Areas for the United States.” Agriculture and Rural Economy Division Research Service, U.S. Department of Agriculture Staff Report No. AGES870721 (August 1987).

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INDEX OF CHARTS AND TABLES ESTIMATING THE TOTAL LABORFORCE POTENTIAL

Table 1 Estimated Total Potential Labor Force – Iowa City Laborshed Area 3 PRIMARY INDUSTRIES OF THE LABORSHED

Chart 1 Where the Employed are Working 7 WORKFORCE STATISTICS

Chart 2 Employment Status of Survey Respondents 8 Chart 3 Type of Employment 9 Table 2 Educational Fields of Study 9 Table 3 Estimated Workforce by Occupation 10 Table 4 Occupational Categories by Gender 10 Table 5 Occupational Categories Across the Zones 11 Table 6 Median Wages & Salaries by Industry 11 Table 7 Median Wages & Salaries by Occupational Category 12

ANALYSIS OF THOSE EMPLOYED WILLING TO CHANGE EMPLOYMENT

Table 8 Totals by Zone 13 Table 9 Estimated Totals by Zone & Gender 14 Table 10 Age Range Distribution 14 Table 11 Educational Fields of Study 15 Table 12 Estimated Workforce by Occupation 16 Table 13 Occupational Categories by Gender 16 Table 14 Occupational Categories Across the Zones 17 Table 15 Desired Occupational Categories Within the Zones 17 Table 16 Comparison of Current Wage Data 18 Table 17 Wage Threshold by Industry 18 Table 18 Comparison of Lowest Wages Considered by Gender 19 Table 19 Underemployed Due to Inadequate Hours Worked 22 Table 20 Underemployed Due to Mismatch of Skills 23 Table 21 Underemployed Due to Low Income 24 Table 22 Total Estimated Underemployed 24

WILLINGNESS OF THOSE NOT CURRENTLY EMPLOYED TO ACCEPT EMPLOYMENT

Table 23 Unemployed - Wiling to Accept Employment 26 Table 24 Homemakers - Willing to Accept Employment 29 Table 25 Retired (18 to 64) - Willing to Accept Employment 30

Publication of: Iowa Workforce Development

Research & Strategic Initiatives Unit 1000 E. Grand Avenue

Des Moines, Iowa 50319 (515) 281-7505

www.iowaworkforce.org

20Report%20with%20Cover%20-%20Iowa%20City

Documents

place of residence

iowa city laborshed

laborshed data

workforce statistics

available labor force

local development officials

local development efforts

labor market areas